From 3aaff37628f93c3198b8966b7c58a75d38058486 Mon Sep 17 00:00:00 2001 From: michal367 Date: Wed, 21 Feb 2024 17:10:55 +0100 Subject: [PATCH 01/25] add building documentation to setup scripts --- setup.bat | 13 +++++++++++++ setup.sh | 14 ++++++++++++++ 2 files changed, 27 insertions(+) diff --git a/setup.bat b/setup.bat index 78b7c98..bde525b 100644 --- a/setup.bat +++ b/setup.bat @@ -21,6 +21,8 @@ set BUILD_PERFORMANCE_TESTING=OFF set REF_IMG=img_reference.dcm set EVAL_IMG=img_evaluated.dcm +set BUILD_DOCUMENTATION=OFF + set INSTALL=OFF set INSTALL_DIR=./yagit @@ -90,6 +92,17 @@ if %BUILD_PERFORMANCE_TESTING% == ON ( ) +@REM ============================================================ +if %BUILD_DOCUMENTATION% == ON ( + echo: + echo BUILDING DOCUMENTATION... + cd docs + doxygen + make html + echo DOCUMENTATION MAIN PAGE: %cd:\=/%/docs/build/html/index.html +) + + @REM ============================================================ if %INSTALL% == ON ( echo: diff --git a/setup.sh b/setup.sh index 85f97f7..7017846 100755 --- a/setup.sh +++ b/setup.sh @@ -25,6 +25,8 @@ BUILD_PERFORMANCE_TESTING=OFF REF_IMG=img_reference.dcm EVAL_IMG=img_evaluated.dcm +BUILD_DOCUMENTATION=OFF + INSTALL=OFF INSTALL_DIR=./yagit @@ -146,6 +148,18 @@ if [ $BUILD_PERFORMANCE_TESTING == ON ]; then fi +# ============================================================ +if [ $BUILD_DOCUMENTATION == ON ]; then + echo "" + echo "BUILDING DOCUMENTATION..." + cd docs + doxygen + make html + cd .. + echo DOCUMENTATION MAIN PAGE: $(pwd)/docs/build/html/index.html +fi + + # ============================================================ if [ $INSTALL == ON ]; then echo "" From e7b5cbc931fdd2e65fad01a3cc9fc31f4de587bb Mon Sep 17 00:00:00 2001 From: michal367 Date: Wed, 28 Feb 2024 22:21:56 +0100 Subject: [PATCH 02/25] add documentation part 1 --- docs/source/_static/.gitkeep | 0 docs/source/_static/css/style.css | 59 + docs/source/_static/images/flow_diagram.svg | 3 + .../_static/images/gamma_index_example.svg | 3 + .../source/_static/images/wendling_circle.svg | 3 + .../images/wendling_circle_distances.svg | 3 + docs/source/_static/images/yf_16threads.svg | 1539 +++++++++++++++ docs/source/_static/images/yfp_1thread.svg | 1721 +++++++++++++++++ docs/source/algorithms.rst | 126 ++ docs/source/authors.rst | 2 - docs/source/conf.py | 9 +- docs/source/data_representation.rst | 2 + docs/source/gamma_index.rst | 147 ++ docs/source/gamma_index_parameters.rst | 2 + docs/source/index.rst | 15 +- docs/source/input_and_output_data.rst | 10 + docs/source/introduction.rst | 122 ++ 17 files changed, 3759 insertions(+), 7 deletions(-) delete mode 100644 docs/source/_static/.gitkeep create mode 100644 docs/source/_static/css/style.css create mode 100644 docs/source/_static/images/flow_diagram.svg create mode 100644 docs/source/_static/images/gamma_index_example.svg create mode 100644 docs/source/_static/images/wendling_circle.svg create mode 100644 docs/source/_static/images/wendling_circle_distances.svg create mode 100644 docs/source/_static/images/yf_16threads.svg create mode 100644 docs/source/_static/images/yfp_1thread.svg delete mode 100644 docs/source/authors.rst create mode 100644 docs/source/data_representation.rst create mode 100644 docs/source/gamma_index.rst create mode 100644 docs/source/gamma_index_parameters.rst create mode 100644 docs/source/input_and_output_data.rst diff --git a/docs/source/_static/.gitkeep b/docs/source/_static/.gitkeep deleted file mode 100644 index e69de29..0000000 diff --git a/docs/source/_static/css/style.css b/docs/source/_static/css/style.css new file mode 100644 index 0000000..d98eb55 --- /dev/null +++ b/docs/source/_static/css/style.css @@ -0,0 +1,59 @@ +.wy-nav-content { + background: white; +} + +figure { + margin-bottom: 20px !important; +} + +figure img { + margin-bottom: 10px; +} + +figure p { + margin-bottom: 0; +} + +figure p a.headerlink { + display: none !important; +} + +ul.list, +ol.list { + margin-top: -18px; +} + +ol.list ol, +ul.list ul, +ol.list ul, +ul.list ol { + margin-bottom: 10px !important; + margin-left: 15px; +} + +ol.list li > p, +ul.list li > p { + margin-bottom: 5px !important; +} + +ol.list li > blockquote, +ul.list li > blockquote { + margin: 0 0 5px 0; +} + +table.center-headers th { + text-align: center; + vertical-align: middle; +} + +table.right-align-vals td:not(:first-child) { + text-align: right; +} + +.math.math-left { + text-align: left; +} + +.math.math-left mjx-container.MathJax { + text-align: left; +} diff --git a/docs/source/_static/images/flow_diagram.svg b/docs/source/_static/images/flow_diagram.svg new file mode 100644 index 0000000..c3e6639 --- /dev/null +++ b/docs/source/_static/images/flow_diagram.svg @@ -0,0 +1,3 @@ + + +
Algorithm calculating the gamma index
Algorithm calculating...
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Input data
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criteria)
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2D gamma index – 3%G/3mm
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Wendling method is much faster than Classic method. + + Classic method -------------- +Classic method was introduced with the paper that introduced gamma index concept by Low et al. [1]_ in 1998. +This is a brute-force method, and because of that, it is very slow. It is based on calculating +gamma function for each pair of points in reference image and evaluated image. This results in a time complexity of +:math:`O(n^k * n^k) = O(n^{2k})`, where :math:`n` is the size of each axis of the input data and :math:`k` is the +dimensionality of the data. For example 3D gamma index has :math:`O(n^6)` time complexity. + + +The subsequent steps of the algorithm are as follows: + +.. rst-class:: list + +#. For each reference point :math:`\vec{r_r}` calculate gamma index :math:`\gamma(\vec{r_r})`: + + A. For each evaluated point :math:`\vec{r_e}` calculate gamma function :math:`\Gamma(\vec{r_r}, \vec{r_e})`. + B. Choose the minimum value of calculated :math:`\Gamma(\vec{r_r}, \vec{r_e})` + as the gamma index :math:`\gamma(\vec{r_r})`. + +#. In the end, the gamma index image is obtained. + + +To speed up these calculations for 3D images, a 2.5D method was introduced, which involves calculating the gamma index +in 2D version for each slice of the 3D image separately. This results in a time complexity of +:math:`O(n^3 * n^2) = O(n^5)`. Unfortunately, it returns less accurate results. + +A commonly used step in classic method to obtain more accurate results is the interpolation of evaluated image +before initiating gamma index calculations. This results in larger input data, further increasing the computation time. +Low and Dempsey propose that spacing in the evaluated image should be less than or equal to :math:`\frac{1}{3}` +of the DTA acceptance criterion [2]_. Wendling method --------------- +In 2007, a new fast method was introduced by Wendling et al. [3]_. +It is based on limiting the searched area in the evaluated image to a circle (in the case of 2D and 2.5D version) +or a sphere (in the case of 3D version). +There is a higher probability of finding the minimum value of the gamma function in the vicinity of the reference point +than in some distant place. + + +.. figure:: _static/images/wendling_circle.svg + :alt: Circle with a radius of the maximum search distance used in Wendling method + :align: center + :scale: 133% + + Limited area (circle) on a 2D evaluated image. Gamma function is calculated only for black points. + +Such a limited area has a maximum search radius and step size, which are parameters of this method. +Evaluated points, which are checked, are located on a grid with intervals equal to the step size, +and their distance from the center does not exceed the search radius. +Wendling et al. propose that the step size should be around :math:`\frac{1}{10}` of the DTA acceptance criterion +for precise results. +The values at points that do not exist in the evaluated image are determined on-the-fly using interpolation +(e.g. bilinear for 2D and trilinear for 3D). + +Some optimizations of on-the-fly interpolation can be achieved by resampling the evaluated image onto the grid +of the reference image before initiating gamma index calculations. +However, YAGIT doesn't perform this step due to two reasons that can lead to less accurate results. +Firstly, this approach involves double interpolation - first during the resampling process +and second during on-the-fly interpolation. +Second interpolation uses interpolated points from first interpolation, which can result in less accurate calculations. +Another reason is the fact that the evaluated image we start with can have a denser grid than the reference image, +and by resampling it, we would lose a lot of information. + + +.. figure:: _static/images/wendling_circle_distances.svg + :alt: Squared distances in circle used in Wendling method + :align: center + :scale: 133% + + Squared distances from the center in limited area (circle) on a 2D evaluated image. + +An important part of this method is the order of the traversing through points in the limited area. +We start from the point at the center of the circle/sphere and traverse through subsequent points that are +increasingly distant from the center. +This order and the squared distances only need to be calculated once -- at the very beginning -- +and then used thereafter. + +Significant speedup can be achieved by stopping the search when it is no longer possible for subsequent points +to yield a smaller value of the gamma function, which occurs when :math:`\frac{r(\vec{r_r}, \vec{r_e})}{\Delta d}` +is greater than or equal to the current minimum value of the gamma function :math:`\Gamma` for :math:`\vec{r_r}`. + + +The subsequent steps of the algorithm are as follows: + +.. rst-class:: list + +#. Resample the evaluated image onto the grid of the reference image (YAGIT doesn't do this). +#. Create a list of points located within the circle/sphere, sorted in ascending order by their distance from the center + of the circle/sphere. +#. For each reference point :math:`\vec{r_r}` calculate gamma index :math:`\gamma(\vec{r_r})` searching within + the limited region on the evaluated image: + + A. Start searching in :math:`\vec{r_e} = \vec{r_r}` and move through the previously created list of points, + which are increasingly further from the initial point: + + a. If the value :math:`r(\vec{r_r}, \vec{r_e}) / \Delta d` is greater than or equal to the current minimum + found value of the gamma function :math:`\Gamma` for :math:`\vec{r_r}`, then stop the search. + b. Determine the value at the point :math:`\vec{r_e}` using interpolation. + c. Calculate the value of the gamma function :math:`\Gamma(\vec{r_r}, \vec{r_e})`. + + B. Choose the minimum value of calculated :math:`\Gamma(\vec{r_r}, \vec{r_e})` + as the gamma index :math:`\gamma(\vec{r_r})`. + +#. In the end, the gamma index image is obtained. + + +The time complexity of such an algorithm is :math:`O(n^k * m^k)`, +where :math:`n` is the number of voxels along each axis, +:math:`k` is the dimensionality of the data +and :math:`m`` is the number of points along the radius of the circle/sphere. +Typically, the algorithm only traverses through a small portion of points within the circle/sphere, +so the average complexity is better. + + +References +---------- + +.. [1] D. A. Low, W. B. Harms, S. Mutic, and J. A. Purdy, + “A technique for the quantitative evaluation of dose distributions,” + Medical Physics, vol. 25, no. 5, pp. 656-661, 1998. + +.. [2] D. A. Low and J. F. Dempsey, + “Evaluation of the gamma dose distribution comparison method,” + Medical Physics, vol. 30, no. 9, pp. 2455-2464, 2003. +.. [3] M. Wendling, L. Zijp, L. McDermott, E. Smit, J.-J. Sonke, B. Mijnheer, and M. Herk, + “A fast algorithm for gamma evaluation in 3d,” + Medical physics, vol. 34, pp. 1647-54, 06 2007. diff --git a/docs/source/authors.rst b/docs/source/authors.rst deleted file mode 100644 index 8c5f784..0000000 --- a/docs/source/authors.rst +++ /dev/null @@ -1,2 +0,0 @@ -Authors -======= diff --git a/docs/source/conf.py b/docs/source/conf.py index af3b654..b818efe 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -5,8 +5,8 @@ # -- Project information ----------------------------------------------------- project = "Yet Another Gamma Index Tool" -author = f"'{project}' Developers" -copyright = f"2023, {author}" +author = f"YAGIT Developers" +copyright = f"2023-2024, {author}" # -- General configuration --------------------------------------------------- @@ -30,3 +30,8 @@ # breathe_debug_trace_directives = True # breathe_debug_trace_doxygen_ids = True # breathe_debug_trace_qualification = True + + +# -- Sphinx setup ------------------------------------------------------------ +def setup(app): + app.add_css_file("css/style.css") diff --git a/docs/source/data_representation.rst b/docs/source/data_representation.rst new file mode 100644 index 0000000..de7ac24 --- /dev/null +++ b/docs/source/data_representation.rst @@ -0,0 +1,2 @@ +Data representation +=================== diff --git a/docs/source/gamma_index.rst b/docs/source/gamma_index.rst new file mode 100644 index 0000000..8451f3d --- /dev/null +++ b/docs/source/gamma_index.rst @@ -0,0 +1,147 @@ +Gamma index +=========== + +The gamma index was proposed by Low et al. [1]_ in 1998. +It combines two other simpler methods: Dose Difference (DD) and Distance To Agreement (DTA). + + +Dose Difference +--------------- + +DD is based on calculating the dose difference at corresponding points :math:`\vec{r_e}` and :math:`\vec{r_r}` +located respectively on the evaluated image :math:`D_e` and the reference image :math:`D_r`. + +.. math:: + \delta(\vec{r_r}, \vec{r_e}) = D_e(\vec{r_e}) - D_r(\vec{r_r}) + +Its acceptance criterion is expressed in percentages [%]. It is related to global or local value: + +.. rst-class:: list + +- global - a predetermined value, typically the maximum value in the reference image, +- local - value at the current point in the reference image. + +If DD value at :math:`\vec{r_r}` point is at most the value of acceptance criterion (e.g. 3%, global), +then this point passes the test. Otherwise it fails. + +The drawback of this test is that it struggles with high gradient regions, as small shifts in the spatial +distribution of radiation doses can result in large DD values. + + +Distance To Agreement +--------------------- + +DTA, on the other hand, is determined by calculating the distance between two closest points with the same dose +on the two images. + +.. math:: + r(\vec{r_r}, \vec{r_e}) = | \vec{r_e} - \vec{r_r} |, +.. math:: + where\ \ D_e(\vec{r_e}) = D_r(\vec{r_r}) + +Its acceptance criterion is expressed in milimeters [mm]. +If DTA value at :math:`\vec{r_r}` point is at most the value of acceptance criterion (e.g. 3 mm), +then this point passes the test. Otherwise it fails. + +The drawback of this method is that it encounters difficulties in low gradient areas, +where minor dose misalignments may require large search radius (large DTA value). + + +Gamma function and gamma index +------------------------------ + +To overcome disadvantages of DD and DTA, the gamma index was developed. +Before calculating it, it is necessary to first determine the gamma function, which combines DD and DTA. + +.. math:: + \Gamma(\vec{r_r}, \vec{r_e}) = + \sqrt{\frac{\delta^2(\vec{r_r}, \vec{r_e})}{\Delta D ^2} + \frac{r^2(\vec{r_r}, \vec{r_e})}{\Delta d ^2}} + +:math:`\Delta D` and :math:`\Delta d` are acceptance criteria of DD and DTA, respectively. +The commonly used criteria values are 3%/3mm with global normalization, abbreviated as 3%G/3mm. + +Now, to obtain the gamma index value for a single reference point, one must select the minimum value +of the gamma function :math:`\Gamma` for that point and all evaluated points. + +.. math:: + \gamma(\vec{r_r}) = \min_{\vec{r_e}}\Gamma(\vec{r_r}, \vec{r_e}) + +It is calculated for each reference point, and in the end, the image containing gamma index values is obtained. +It has the same size as the reference image. + + +GIPR +---- + +The Gamma Index Passing Rate (GIPR) is a measure indicating how many points passed the test -- +that is, how many gamma index values are less than or equal to 1. + +.. math:: + GIPR = \frac{| \{\gamma(\vec{r_r}) \le 1\} |}{| \{\gamma(\vec{r_r})\} |} + +When this value is sufficiently high (e.g. 90%), it can be considered that +the two compared images are sufficiently similar to each other. + + +Flow diagram +------------ + +.. figure:: _static/images/flow_diagram.svg + :alt: Flow diagram of gamma index + :align: center + +The figure shows the successive stages of the gamma index calculations. +GIPR is an optional step that provides a simple single metric, but analyzing the gamma index image can provide +a lot more information about the result. + + +Example +------- + +To ilustrate how the gamma index works, a simple example is presented here. +It is calculated for two-dimensional images, each containing only 4 elements. + +Used parameters are: 3% with global normalization for DD acceptance criterion and 3 mm for DTA acceptance criterion. + +.. figure:: _static/images/gamma_index_example.svg + :alt: Example of calculating 2D gamma index - 3%G/3mm + :align: center + +Below are the calculations of gamma index image values. +Note that some of the gamma function calculations are skipped, and only minimum values are shown. + +.. rst-class:: math-left +.. math:: + \gamma(\vec{r_{r0}}) = \Gamma(\vec{r_{r0}}, \vec{r_{e0}}) = + \sqrt{\frac{(0.93 - 0.93)^2}{(0.03*1.00)^2} + \frac{(0 - (-1))^2 + (1 - 0)^2}{3^2}} \approx + \sqrt{0 + 0.222} \approx 0.471 + +.. rst-class:: math-left +.. math:: + \gamma(\vec{r_{r1}}) = \Gamma(\vec{r_{r1}}, \vec{r_{e1}}) = + \sqrt{\frac{(0.96 - 0.95)^2}{(0.03*1.00)^2} + \frac{(2 - 1)^2 + (1 - 0)^2}{3^2}} \approx + \sqrt{0.111 + 0.222} \approx 0.577 + +.. rst-class:: math-left +.. math:: + \gamma(\vec{r_{r2}}) = \Gamma(\vec{r_{r2}}, \vec{r_{e1}}) = + \sqrt{\frac{(0.96 - 0.97)^2}{(0.03*1.00)^2} + \frac{(2 - (-1))^2 + (1 - 2)^2}{3^2}} \approx + \sqrt{0.111 + 1.111} \approx 1.106 + +.. rst-class:: math-left +.. math:: + \gamma(\vec{r_{r3}}) = \Gamma(\vec{r_{r3}}, \vec{r_{e3}}) = + \sqrt{\frac{(1.02 - 1.00)^2}{(0.03*1.00)^2} + \frac{(2 - 1)^2 + (3 - 2)^2}{3^2}} \approx + \sqrt{0.444 + 0.222} \approx 0.816 + +.. rst-class:: math-left +.. math:: + GIPR = \frac{3}{4} = 75\% + + +References +---------- + +.. [1] D. A. Low, W. B. Harms, S. Mutic, and J. A. Purdy, + “A technique for the quantitative evaluation of dose distributions,” + Medical Physics, vol. 25, no. 5, pp. 656-661, 1998. diff --git a/docs/source/gamma_index_parameters.rst b/docs/source/gamma_index_parameters.rst new file mode 100644 index 0000000..78f8975 --- /dev/null +++ b/docs/source/gamma_index_parameters.rst @@ -0,0 +1,2 @@ +Gamma index parameters +====================== diff --git a/docs/source/index.rst b/docs/source/index.rst index 1c3e696..96f0301 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -2,11 +2,20 @@ Yet Another Gamma Index Tool |release| documentation ==================================================== .. toctree:: - :maxdepth: 2 + :maxdepth: 1 + :caption: Getting Started introduction - installation + gamma_index algorithms - authors + gamma_index_parameters + input_and_output_data + data_representation + +.. toctree:: + :maxdepth: 1 + :caption: Usage + + installation api/api examples diff --git a/docs/source/input_and_output_data.rst b/docs/source/input_and_output_data.rst new file mode 100644 index 0000000..d86a02b --- /dev/null +++ b/docs/source/input_and_output_data.rst @@ -0,0 +1,10 @@ +Input and output data +===================== + + +Input data +---------- + + +Output data +----------- diff --git a/docs/source/introduction.rst b/docs/source/introduction.rst index c516b33..3497159 100644 --- a/docs/source/introduction.rst +++ b/docs/source/introduction.rst @@ -1,2 +1,124 @@ Introduction ============ + +YAGIT (Yet Another Gamma Index Tool) is an efficient open-source library for calculating gamma index. +It can be used for comparison of two images (reference image and evaluated image) containing +2D or 3D radiation dose distributions. It is written in C++ and works on Linux and Windows. + + +Main functionalities +-------------------- + +Most important features of YAGIT are: + +.. rst-class:: list + +- two methods of gamma index calculation: classic and Wendling, +- four implementations of classic method (sequential, multithreaded, SIMD, multithreaded + SIMD), +- two implementations of Wendling method (sequential, multithreaded), +- three versions of gamma index: 2D, 2.5D and 3D, +- reading input files (DICOM and MetaImage), +- saving data and results to output file (MetaImage), +- linear, bilinear and trilinear interpolation of data. + +Performance +----------- + +The performance of YAGIT has been compared with the performance of `FRED`_ and `PyMedPhys`_. +Gamma index module of FRED has been tested using `FRED tools`_ that calls FRED functions underneath. + +.. _FRED: https://www.fred-mc.org/ +.. _FRED tools: https://github.com/jasqs/FREDtools +.. _PyMedPhys: https://github.com/pymedphys/pymedphys + +Performance tests have been executed on a machine with an AMD Ryzen 7 5800H processor, +which has a clock speed of 3.2 GHz, featuring 8 cores and 16 threads. Machine has 16 GB of RAM DDR4 3200 MHz. + +It has been tested on Windows 11 Home 64-bit (version 22H2) operating system with WSL2 and Ubuntu 22.04.2 LTS. +FRED's gamma index module requires Linux, so all tools have been tested on WSL to maintain identical environment. + +This system contains gcc and g++ compilers in version 11.4.0 with glibc 2.35 and libstdc++ 3.4.30, CMake 3.22.1 +and Python 3.10.12. + +Tested versions of tools are: + +.. rst-class:: list + +- YAGIT built from 51d34ae commit (05.09.2023) using CMake tool in Release mode and g++ compiler, +- FRED tools 0.6.79 with libFredGI.so 4.2, +- PyMedPhys 0.39.3. + +Two 3D DICOM images has been used in the tests. The reference image has dimensions of 198x198x198, +while the evaluated image has dimensions of 200x200x200. They are very similar (GIPR ~ 99%). + + +.. rst-class:: center-headers right-align-vals +.. table:: + :align: center + + +------------+----------------------------------------------------------------+ + | | Average time [s] | + | +-------------------------+-------------------------+------------+ + | DD/DTA | YAGIT | FRED | PyMedPhys | + | +------------+------------+------------+------------+------------+ + | | 1 thread | 16 threads | 1 thread | 16 threads | 1 thread | + +============+============+============+============+============+============+ + | Wendling method -- 3D | + +------------+------------+------------+------------+------------+------------+ + | 3\%G/3mm | 3.022 | 0.363 | 7.991 | 1.078 | 200.822 | + +------------+------------+------------+------------+------------+------------+ + | 2\%G/2mm | 8.637 | 1.021 | 21.472 | 2.598 | 445.684 | + +------------+------------+------------+------------+------------+------------+ + | 3\%L/3mm | 3.534 | 0.427 | 9.145 | 1.238 | 224.542 | + +------------+------------+------------+------------+------------+------------+ + | 2\%L/2mm | 9.618 | 1.183 | 23.895 | 2.878 | 498.518 | + +------------+------------+------------+------------+------------+------------+ + +The table shows comparison of calculation times between YAGIT, FRED and PyMedPhys. +Other parameters: normalizing dose = max. reference image dose, dose cutoff = 5%, +search radius = 3*DTA, step size = DTA/10. + +When using 16 threads, YAGIT and FRED speed up about 8 times. +It is 8, not 16, because the CPU on which it has been run has 8 cores. +16 threads have been used to achieve better speedup due to simultaneous multithreading (SMT). +PyMedPhys has been tested only with one thread, because it doesn't support multithreaded gamma index. + + +.. figure:: _static/images/yfp_1thread.svg + :alt: Single-threaded gamma index using Wendling method + :align: center + +First image shows differences in computation times between single-threaded YAGIT, FRED and PyMedPhys. +YAGIT is about 2.5 times faster than FRED and about 50--70 times faster than PyMedPhys. + + +.. figure:: _static/images/yf_16threads.svg + :alt: Multi-threaded gamma index using Wendling method + :align: center + +Second image shows differences in computation times between multi-threaded YAGIT and FRED. +YAGIT is about 2--3 times faster than FRED. + + +.. rst-class:: center-headers right-align-vals +.. table:: + :align: center + + +------------+--------------------------------------+ + | | GIPR [%] | + | DD/DTA +------------+------------+------------+ + | | YAGIT | FRED | PyMedPhys | + +============+============+============+============+ + | Wendling method -- 3D | + +------------+------------+------------+------------+ + | 3\%G/3mm | 99.960 | 99.960 | 99.967 | + +------------+------------+------------+------------+ + | 2\%G/2mm | 99.144 | 99.145 | 99.232 | + +------------+------------+------------+------------+ + | 3\%L/3mm | 99.959 | 99.959 | 99.966 | + +------------+------------+------------+------------+ + | 2\%L/2mm | 99.049 | 99.050 | 99.025 | + +------------+------------+------------+------------+ + +In this table, it can be noticed that the values of GIPR in YAGIT and FRED are nearly identical. +However, PyMedPhys returns values that slightly differ from the other two tools. 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0.93
0.93
0.95
0.95
0.97
0.97
1.00
1.00
Reference image
Reference image
x = -1
x = -1
x = 1
x = 1
y = 0
y = 0
y = 2
y = 2
0.93
0.93
0.96
0.96
0.90
0.90
1.02
1.02
Evaluated image
Evaluated image
x = 0
x = 0
x = 2
x = 2
y = 1
y = 1
y = 3
y = 3
0.471
0.471
0.577
0.577
1.106
1.106
0.816
0.816
Gamma index image
Gamma index image
x = -1
x = -1
x = 1
x = 1
y = 0
y = 0
y = 2
y = 2
2D gamma index – 3%G/3mm
2D gamma index – 3%G/3mmText is not SVG - cannot display \ No newline at end of file +
0.93
0.93
0.95
0.95
0.97
0.97
1.00
1.00
Reference image
Reference image
x = -1
x = -1
x = 1
x = 1
y = 0
y = 0
y = 2
y = 2
0.93
0.93
0.96
0.96
0.90
0.90
1.02
1.02
Evaluated image
Evaluated image
x = 0
x = 0
x = 2
x = 2
y = 1
y = 1
y = 3
y = 3
0.471
0.471
0.577
0.577
1.106
1.106
0.816
0.816
Gamma index image
Gamma index image
x = -1
x = -1
x = 1
x = 1
y = 0
y = 0
y = 2
y = 2
2D gamma index – 3%G/3mm
2D gamma index – 3%G/3mm \ No newline at end of file diff --git a/docs/source/_static/images/image_planes.svg b/docs/source/_static/images/image_planes.svg new file mode 100644 index 0000000..88c9898 --- /dev/null +++ b/docs/source/_static/images/image_planes.svg @@ -0,0 +1,3 @@ + + +
z
z
y
y
x
x
Axial
I → S
AxialI → S
Coronal
A → P
Coronal...
Sagittal
R → L
Sagittal...
LPS
LPS \ No newline at end of file diff --git a/docs/source/_static/images/position_and_spacing.svg b/docs/source/_static/images/position_and_spacing.svg new file mode 100644 index 0000000..cb887d5 --- /dev/null +++ b/docs/source/_static/images/position_and_spacing.svg @@ -0,0 +1,3 @@ + + +
(0, 0)
(0, 0)
(Tx, Ty)
(Tx, T...
Sx
Sx
Sy
Sy
y
y
x
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10 \ No newline at end of file diff --git a/docs/source/algorithms.rst b/docs/source/algorithms.rst index 1ffa096..c14fb6f 100644 --- a/docs/source/algorithms.rst +++ b/docs/source/algorithms.rst @@ -53,6 +53,7 @@ than in some distant place. :scale: 133% Limited area (circle) on a 2D evaluated image. Gamma function is calculated only for black points. + Values at those points are interpolated on-the-fly. Such a limited area has a maximum search radius and step size, which are parameters of this method. Evaluated points, which are checked, are located on a grid with intervals equal to the step size, @@ -65,7 +66,7 @@ The values at points that do not exist in the evaluated image are determined on- Some optimizations of on-the-fly interpolation can be achieved by resampling the evaluated image onto the grid of the reference image before initiating gamma index calculations. However, YAGIT doesn't perform this step due to two reasons that can lead to less accurate results. -Firstly, this approach involves double interpolation - first during the resampling process +Firstly, this approach involves double interpolation -- first during the resampling process and second during on-the-fly interpolation. Second interpolation uses interpolated points from first interpolation, which can result in less accurate calculations. Another reason is the fact that the evaluated image we start with can have a denser grid than the reference image, diff --git a/docs/source/data_representation.rst b/docs/source/data_representation.rst index de7ac24..b00fd96 100644 --- a/docs/source/data_representation.rst +++ b/docs/source/data_representation.rst @@ -1,2 +1,219 @@ Data representation =================== + +Coordinate system +----------------- + +DICOM and MetaImage use patient (anatomical) coordinate system that is relative to the patient. +If patient orientation on the couch is changed, then the patient coordinate system is rotated accordingly. +Other alternatives are the couch (fixed, room) coordinate system and the beam (gantry) coordinate system. + +.. figure:: _static/images/coordinate_system.svg + :alt: DICOM LPS coordinate system + :align: center + :scale: 135% + + Directions and LPS coordinate system relative to a patient. + + L -- Left, R -- Right, A -- Anterior, P -- Posterior, S -- Superior, I -- Inferior. + +Specifically, DICOM uses LPS (right to Left, anterior to Posterior, inferior to Superior) coordinate system. +MetaImage uses the same system, but it denotes it as RAI (Right to left, Anterior to posterior, Inferior to superior). +YAGIT also uses this system. + +The three-letter coordinate system defines the axis directions as well as their order. +The first letter corresponds to the x-axis, the second to the y-axis, and the third to the z-axis. +For example, in the LPS system: L=x, P=y, S=z, and in the SLP system: S=x, L=y, P=z. + + +Image planes +------------ + +The 3D image can be viewed from three perspectives: axial, coronal and sagittal. +Axial (also known as transverse or horizontal) separates the superior from the inferior. +Coronal (also known as frontal) separates the anterior from the posterior. +Sagittal (also known as longitudinal) separates the left from the right. + +.. figure:: _static/images/image_planes.svg + :alt: Image planes (axial, coronal and sagittal) + :align: center + :scale: 135% + + 3D image planes -- axial, coronal and sagittal -- with coordinates consistent with LPS. + The black filled squares represent the first voxel of an image. + + +The i'th column, j'th row and k'th frame map to the coordinates xyz for the respective planes as follows: + +.. rst-class:: list list-math-right + +- Axial: :math:`ijk \rightarrow xyz` +- Coronal: :math:`ijk \rightarrow xzy` +- Sagittal: :math:`ijk \rightarrow yzx` + +A 3D image is stored in a file slice-by-slice using one out of three planes. +The plane used depends on the third letter of the coordinate system: +S or I for axial, A or P for coronal, L or R for sagittal. +In the LPS coordinate system, slices are stored using the axial plane. + +Note that when calculating the gamma index, YAGIT does not take into account whether the plane of the image was changed +after reading from a file. +It treats all images as if they were stored in the axial plane. + + +Image position and voxel spacing +-------------------------------- + +Image position refers to the coordinates x, y, z of the first voxel of the image, expressed in millimeters. +It determines the offset from the point (0, 0, 0), which is related to the treatment machine, +and it is the intersection point of the x, y, and z axes. + +Voxel spacing specifies the distances between adjacent voxels along each axis in millimeters. +Alternatively, it can be viewed as the size of a voxel. +The voxel spacing can have different values for each axis, +but if all three spacings are equal, the image is said to have isotropic voxel spacing. + +Additionally, DICOM allows for unevenly distributed spacing along the z-axis (spacing between slices), +as the spacing may be greater in areas that are farther from the main region of interest. +YAGIT doesn't support this kind of images. + +.. figure:: _static/images/position_and_spacing.svg + :alt: Image position and voxel spacing + :align: center + :scale: 130% + + Example of image position and pixel spacing for a 2D image. + + :math:`T_x, T_y` -- image position, :math:`S_x, S_y` -- pixel spacing. + + +Image orientation +----------------- + +The image orientation indicates how the patient is positioned on the couch -- +whether lying on their back, stomach, or side, +and whether they are oriented head-first or feet-first towards the machine. +The most basic orientation is HFS (Head First Supine). +In this case, the patient is positioned head-first towards the machine and lying on their back. + +The image orientation is provided in the form of direction cosines of the first row and the first column, +as well as the normal vector to these two directions. + +.. math:: + \vec{v_r} = + \begin{bmatrix} + A_x \\ + A_y \\ + A_z + \end{bmatrix} + ,\ \ \ + \vec{v_c} = + \begin{bmatrix} + B_x \\ + B_y \\ + B_z + \end{bmatrix} + ,\ \ \ + \vec{v_n} = + \vec{v_r} \times \vec{v_c} = + \begin{bmatrix} + C_x \\ + C_y \\ + C_z + \end{bmatrix} + +They are often written in the form of a single vector. + +.. math:: + \vec{v} = + \begin{bmatrix} A_x & A_y & A_z; & B_x & B_y & B_z; & C_x & C_y & C_z \end{bmatrix} + + +There are 8 basic image orientations: + +.. rst-class:: list list-code-right + +- HFS -- Head First Supine ``[ 1 0 0; 0 1 0; 0 0 1]`` +- HFP -- Head First Prone ``[-1 0 0; 0 -1 0; 0 0 1]`` +- HFDL -- Head First Decubitus Left ``[ 0 -1 0; 1 0 0; 0 0 1]`` +- HFDR -- Head First Decubitus Right ``[ 0 1 0; -1 0 0; 0 0 1]`` +- FFS -- Feet First Supine ``[-1 0 0; 0 1 0; 0 0 -1]`` +- FFP -- Feet First Prone ``[ 1 0 0; 0 -1 0; 0 0 -1]`` +- FFDL -- Feet First Decubitus Left ``[ 0 1, 0; 1 0 0; 0 0 -1]`` +- FFDR -- Feet First Decubitus Right ``[ 0 -1 0; -1 0 0; 0 0 -1]`` + +YAGIT supports only the HFS image orientation, for now. + + +Calculating xyz coordinates +--------------------------- + +To determine the xyz coordinates from the indices ijk (i'th column, j'th row, k'th frame), +the following formula should be used, +incorporating rotation (image orientation), scaling (pixel spacing) and translation (image position). + +.. math:: + \begin{bmatrix} + x \\ + y \\ + z + \end{bmatrix} + = + \begin{bmatrix} + A_x & B_x & C_x \\ + A_y & B_y & C_y \\ + A_z & B_z & C_z + \end{bmatrix} + \begin{bmatrix} + S_x & 0 & 0 \\ + 0 & S_y & 0 \\ + 0 & 0 & S_z + \end{bmatrix} + \begin{bmatrix} + i \\ + j \\ + k + \end{bmatrix} + + + \begin{bmatrix} + T_x \\ + T_y \\ + T_z + \end{bmatrix} + +| where: +| :math:`A_x, A_y, A_z` -- values from the direction cosine of the first row (x), +| :math:`B_x, B_y, B_z` -- values from the direction cosine of the first column (y), +| :math:`C_x, C_y, C_z` -- values from the normal vector of the image frames (z), +| :math:`S_x, S_y, S_z` -- xyz voxel spacings, +| :math:`T_x, T_y, T_z` -- xyz image positions of the first voxel. + + +This formula can be alternatively expressed using 4x4 affine matrix. + +.. math:: + \begin{bmatrix} + x \\ + y \\ + z \\ + 1 + \end{bmatrix} + = + \begin{bmatrix} + A_x S_x & B_x S_y & C_x S_z & T_x \\ + A_y S_x & B_y S_y & C_y S_z & T_y \\ + A_z S_x & B_z S_y & C_z S_z & T_z \\ + 0 & 0 & 0 & 1 + \end{bmatrix} + \begin{bmatrix} + i \\ + j \\ + k \\ + 1 + \end{bmatrix} + + +Data memory layout +------------------ + +.. TODO diff --git a/docs/source/gamma_index_parameters.rst b/docs/source/gamma_index_parameters.rst deleted file mode 100644 index 78f8975..0000000 --- a/docs/source/gamma_index_parameters.rst +++ /dev/null @@ -1,2 +0,0 @@ -Gamma index parameters -====================== diff --git a/docs/source/index.rst b/docs/source/index.rst index 96f0301..162168e 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -8,7 +8,7 @@ Yet Another Gamma Index Tool |release| documentation introduction gamma_index algorithms - gamma_index_parameters + parameters input_and_output_data data_representation @@ -17,5 +17,5 @@ Yet Another Gamma Index Tool |release| documentation :caption: Usage installation - api/api examples + api/api diff --git a/docs/source/input_and_output_data.rst b/docs/source/input_and_output_data.rst index d86a02b..aa5faf8 100644 --- a/docs/source/input_and_output_data.rst +++ b/docs/source/input_and_output_data.rst @@ -1,10 +1,76 @@ Input and output data ===================== +Algorithms computing the gamma index take two images with radiation dose distributions +and return a single image with gamma index values. + Input data ---------- +The input data for the gamma index calculation algorithm consists of two-dimensional or three-dimensional images +containing the distribution of radiation dose. +Two images are needed for comparison: the reference image (also known as measured) +and the evaluated image (also known as calculated or planned). +Typically, the reference image is obtained from measurements of the actual radiation dose by appropriate detectors. +Meanwhile, the evaluated image usually is the image generated by the Treatment Planning System (TPS). + +.. figure:: _static/images/reference_image_example.png + :alt: Example of a reference image + :align: center + :width: 90% + + Simple reference image with spatial distribution of radiation dose visualized in the `3D Slicer`_ program. + +.. _3D Slicer: https://www.slicer.org/ + +Such data are stored in various file formats. +These include, among others, DICOM (.dcm), MetaImage (.mha, .mhd, .raw), and EGSnrc files (.3ddose). + +YAGIT is able to read DICOM files with radiation dose data (Modality = RTDOSE) and MetaImage files. + + +Key elements of input data +~~~~~~~~~~~~~~~~~~~~~~~~~~ + +The algorithm calculating gamma index requires the following information from the input files: + +.. rst-class:: list + +- radiation dose values +- size -- number of frames, rows, and columns +- offset/position -- the position of the first voxel in the image, expressed in millimeters. + Each axis has its own offset value +- spacing -- the spacing between voxels expressed in millimeters. Each axis has its own spacing value + +In particular, the reference and evaluated images don't have to have the same sizes, offsets, or spacings. + Output data ----------- + +The algorithm outputs an image with gamma index values for each point of the reference image. +The resulting image has the same size, offset, and spacing as the reference image. + +.. figure:: _static/images/gamma_image_example.png + :alt: Example of a gamma index image + :align: center + :width: 90% + + The image with gamma index values calculated for the parameters 3%L/3mm visualized in the `3D Slicer`_ program. + The black areas contain NaN values. + +In YAGIT, the gamma index for reference points that fall below the dose threshold is set to NaN. +The same value is also assigned in the case of local normalization when the algorithm encounters a zero dose value +at a reference point, to avoid division by zero when calculating the gamma function. + +Due to the possibility of the resulting image containing NaN values, +a suitable file format for storing the gamma index image is MetaImage. +This is because MetaImage saves image directly in binary format +for both integers and floating-point numbers (including special values such as NaN and infinity). +DICOM, on the other hand, only stores integers as binary data. +If the image contains floating-point numbers, it needs to convert values before saving +and determine appropriate coefficients that will allow for the reconstruction of the original values, +but this prevents the storage of NaN values and infinity. +The only exception is DICOM Parametric Map, which allows for the direct storage of floating-point numbers, +but YAGIT doesn't support it. diff --git a/docs/source/introduction.rst b/docs/source/introduction.rst index 3497159..36314dd 100644 --- a/docs/source/introduction.rst +++ b/docs/source/introduction.rst @@ -75,7 +75,7 @@ while the evaluated image has dimensions of 200x200x200. They are very similar ( +------------+------------+------------+------------+------------+------------+ The table shows comparison of calculation times between YAGIT, FRED and PyMedPhys. -Other parameters: normalizing dose = max. reference image dose, dose cutoff = 5%, +Other parameters: normalizing dose = max. reference image dose, dose cutoff = 5% of max. reference image dose, search radius = 3*DTA, step size = DTA/10. When using 16 threads, YAGIT and FRED speed up about 8 times. diff --git a/docs/source/parameters.rst b/docs/source/parameters.rst new file mode 100644 index 0000000..b47cb30 --- /dev/null +++ b/docs/source/parameters.rst @@ -0,0 +1,95 @@ +Parameters +========== + +Gamma index is configurable by adjusting its parameters. They impact the results and the computation time. + + +General parameters +------------------ + +Algorithms calculating the gamma index has several parameters: + +.. rst-class:: list + +- DD acceptance criterion :math:`\Delta D` [%], +- DTA acceptance criterion :math:`\Delta d` [mm], +- normalization: + + - global -- a predetermined value, typically the maximum value in the reference image, + - local -- value at the current point in the reference image, + +- dose cutoff (DCO) -- the gamma index will not be calculated for reference points + with radiation dose values below this threshold. + +Frequently used parameters in radiotherapy are values within the range of 1--3% for the acceptance criterion DD +with global normalization and 1--3 mm for the acceptance criterion DTA. +These parameters are shortened, e.g. 3%G/3mm (3% DD criterion, global normalization, 3 mm DTA criterion). + +In YAGIT, in the case of local normalization, when the dose value at the current reference point is 0, +that point is skipped to avoid division by zero. +Similarly, in the case of a dose cutoff value greater than 0, +if a reference point with a value below this threshold is encountered, such a point is also skipped. +In both cases, the gamma index value will be set to NaN. +When calculating GIPR, NaN values are not taken into account in either the numerator or the denominator. + +Wendling method parameters +-------------------------- + +There are also two parameters exclusive to the Wendling method: + +.. rst-class:: list + +- maximum search distance [mm] -- the radius of the circle/sphere that will be searched in the evaluated image, +- step size [mm] -- the spacing between searched points inside the circle/sphere. + +The maximum search distance should be at least equal to the DTA acceptance criterion, +but it is preferable to be several times greater for better gamma index results. +The step size should be :math:`\frac{1}{10}` of the DTA acceptance criterion, +as recommended by the authors of this method, to achieve better results. + +Instead of using maximum search distance, some other tools use the maximum gamma index value. +The relation between these two parameters is as follows + +.. math:: + g = \frac{s}{\Delta d} + +| where: +| :math:`g` -- maximum gamma index value, +| :math:`s` -- maximum search distance, +| :math:`\Delta d` -- DTA acceptance criterion. + + +Impact of parameters changes on computation time +------------------------------------------------ + +DD and DTA +~~~~~~~~~~ + +The change of DD and DTA parameters in the classic method has no impact on the computation time, +because changing them doesn't affect the number of operations performed. + +In Wendling method, the computation time is inversely proportional to the value of the DD criterion +(:math:`t \sim \frac{1}{\Delta D}`) and proportional to the value of the DTA criterion (:math:`t \sim \Delta d`). +The proportionality with the DTA criterion holds true when only the DTA criterion is changed, +without adjusting maximum search distance and step size to it. +Changing DD and DTA acceptance criteria affects when the stopping condition will occur during the search +of the circle/sphere, thus also impacting the computation time. + +Normalization +~~~~~~~~~~~~~ + +In the classical method, changing the normalization from global to local reduces computation time +due to skipping all reference points with a value of 0. +There are many such points (usually around 50%) in an average reference image. + +However, in Wendling method, the runtime increases because when using local normalization +for reference points with small doses, the stopping condition occurs much later. +These problematic points can be skipped by appropriately setting the dose cutoff. + +Dose cutoff +~~~~~~~~~~~ + +Changing the dose cutoff value can significantly affect computation time because typical images contain +a large background region (an area where the dose value is equal to 0) +and numerous low-dose regions (areas where the dose value is relatively low compared to other regions). +In both methods, the larger the dose cutoff, the shorter the computation time. 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x \ No newline at end of file diff --git a/docs/source/data_representation.rst b/docs/source/data_representation.rst index b00fd96..e9aea4b 100644 --- a/docs/source/data_representation.rst +++ b/docs/source/data_representation.rst @@ -6,7 +6,8 @@ Coordinate system DICOM and MetaImage use patient (anatomical) coordinate system that is relative to the patient. If patient orientation on the couch is changed, then the patient coordinate system is rotated accordingly. -Other alternatives are the couch (fixed, room) coordinate system and the beam (gantry) coordinate system. +Other coordinate systems used in radiotherapy are the couch (fixed, room) coordinate system +and the beam (gantry) coordinate system. .. figure:: _static/images/coordinate_system.svg :alt: DICOM LPS coordinate system @@ -43,7 +44,7 @@ Sagittal (also known as longitudinal) separates the left from the right. The black filled squares represent the first voxel of an image. -The i'th column, j'th row and k'th frame map to the coordinates xyz for the respective planes as follows: +The ith column, jth row, kth frame map to the coordinates xyz for the respective planes as follows: .. rst-class:: list list-math-right @@ -148,9 +149,9 @@ YAGIT supports only the HFS image orientation, for now. Calculating xyz coordinates --------------------------- -To determine the xyz coordinates from the indices ijk (i'th column, j'th row, k'th frame), +To determine the xyz coordinates from the indexes ijk (ith column, jth row, kth frame), the following formula should be used, -incorporating rotation (image orientation), scaling (pixel spacing) and translation (image position). +incorporating rotation (image orientation), scaling (voxel spacing) and translation (image position). .. math:: \begin{bmatrix} @@ -213,7 +214,43 @@ This formula can be alternatively expressed using 4x4 affine matrix. \end{bmatrix} -Data memory layout ------------------- +Data indexing and memory order +------------------------------ -.. TODO +Accessing a single voxel in the image is done using the image coordinate system, +where columns, rows, and frames are numbered using indexes. + +In YAGIT, the image indexes are written frame-first, column-last -- +instead of using ijk (ith column, jth row, kth frame) it uses kji (kth frame, jth row, ith column). +It's the same indexing as used in matrices and in most programming languages. + +.. figure:: _static/images/3d_index.svg + :alt: 3D indexing -- (k,j,i) + :align: center + :scale: 130% + + 3D indexing -- (k,j,i) -- in the axial plane. + + +YAGIT stores 2D and 3D images in the form of a linearized one-dimensional array. +It arranges single elements in memory according to the row-major order (in this case it is frame-major order). +DICOM and MetaImage also use this order. + +.. figure:: _static/images/1d_index.svg + :alt: Linear indexing + :align: center + :scale: 130% + + Linear indexing in the axial plane. + + +Data type +--------- + +Image data elements in YAGIT are stored using float (32-bit single precision floating point). +It provides 6--8 significant decimal digits of precision, which is sufficient for gamma index calculations. +In comparison, double (64-bit double precision floating point) provides 15--16 significant decimal digits of precision. + +Thanks to the fact that a float has a size that is two times smaller than a double, +it has two times less memory usage, can fit twice as many elements in the SIMD registers, +and results in fewer cache misses due to more data fitting in the cache. diff --git a/docs/source/input_and_output_data.rst b/docs/source/input_and_output_data.rst index aa5faf8..c341579 100644 --- a/docs/source/input_and_output_data.rst +++ b/docs/source/input_and_output_data.rst @@ -25,7 +25,11 @@ Meanwhile, the evaluated image usually is the image generated by the Treatment P .. _3D Slicer: https://www.slicer.org/ Such data are stored in various file formats. -These include, among others, DICOM (.dcm), MetaImage (.mha, .mhd, .raw), and EGSnrc files (.3ddose). +These include, among others, `DICOM`_ (.dcm), ITK `MetaImage`_ (.mha, .mhd, .raw), and `DOSXYZnrc`_ 3D dose (.3ddose). + +.. _DICOM: https://www.dicomstandard.org/ +.. _MetaImage: https://github.com/Kitware/MetaIO +.. _DOSXYZnrc: https://github.com/nrc-cnrc/EGSnrc YAGIT is able to read DICOM files with radiation dose data (Modality = RTDOSE) and MetaImage files. diff --git a/docs/source/parameters.rst b/docs/source/parameters.rst index b47cb30..b3091bf 100644 --- a/docs/source/parameters.rst +++ b/docs/source/parameters.rst @@ -47,15 +47,15 @@ but it is preferable to be several times greater for better gamma index results. The step size should be :math:`\frac{1}{10}` of the DTA acceptance criterion, as recommended by the authors of this method, to achieve better results. -Instead of using maximum search distance, some other tools use the maximum gamma index value. +Instead of using maximum search distance, some other tools use the maximum gamma searched for. The relation between these two parameters is as follows .. math:: g = \frac{s}{\Delta d} | where: -| :math:`g` -- maximum gamma index value, -| :math:`s` -- maximum search distance, +| :math:`g` -- maximum gamma searched for, so that :math:`\frac{r(\vec{r_r}, \vec{r_e})}{\Delta d} \le g`, +| :math:`s` -- maximum search distance, so that :math:`r(\vec{r_r}, \vec{r_e}) \le s`, | :math:`\Delta d` -- DTA acceptance criterion. From 2d430f5b3b0589edf0756363b09f1fb8c89b5119 Mon Sep 17 00:00:00 2001 From: michal367 Date: Sat, 23 Mar 2024 13:50:28 +0100 Subject: [PATCH 05/25] fix calling make.bat in setup.bat --- setup.bat | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.bat b/setup.bat index bde525b..deda14f 100644 --- a/setup.bat +++ b/setup.bat @@ -98,7 +98,7 @@ if %BUILD_DOCUMENTATION% == ON ( echo BUILDING DOCUMENTATION... cd docs doxygen - make html + call make.bat html echo DOCUMENTATION MAIN PAGE: %cd:\=/%/docs/build/html/index.html ) From ca3e58dd0cc94e2ec32235fe61e76c852aaa8843 Mon Sep 17 00:00:00 2001 From: michal367 Date: Sat, 23 Mar 2024 19:10:56 +0100 Subject: [PATCH 06/25] fix cd in setup.bat --- setup.bat | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/setup.bat b/setup.bat index deda14f..d55bd98 100644 --- a/setup.bat +++ b/setup.bat @@ -93,13 +93,15 @@ if %BUILD_PERFORMANCE_TESTING% == ON ( @REM ============================================================ +set YAGIT_DIR=%cd:\=/% if %BUILD_DOCUMENTATION% == ON ( echo: echo BUILDING DOCUMENTATION... cd docs doxygen call make.bat html - echo DOCUMENTATION MAIN PAGE: %cd:\=/%/docs/build/html/index.html + echo DOCUMENTATION MAIN PAGE: %YAGIT_DIR%/docs/build/html/index.html + cd .. ) From 96d96441ccacaf645dbbb280a566da51c3687e5a Mon Sep 17 00:00:00 2001 From: michal367 Date: Sat, 23 Mar 2024 20:14:45 +0100 Subject: [PATCH 07/25] add installation instructions in documentation --- docs/source/_static/css/style.css | 18 +++ docs/source/gamma_index.rst | 4 +- docs/source/installation.rst | 220 ++++++++++++++++++++++++++++++ 3 files changed, 240 insertions(+), 2 deletions(-) diff --git a/docs/source/_static/css/style.css b/docs/source/_static/css/style.css index f50d8b5..c246b75 100644 --- a/docs/source/_static/css/style.css +++ b/docs/source/_static/css/style.css @@ -41,6 +41,15 @@ ul.list li > blockquote { margin: 0 0 5px 0; } +.code { + margin-top: -18px; +} + +code { + color: #9b2f5f !important; + font-weight: 700; +} + table.center-headers th { text-align: center; vertical-align: middle; @@ -50,6 +59,14 @@ table.right-align-vals td:not(:first-child) { text-align: right; } +table.wrap-text td { + white-space: normal; +} + +table.wrap-text td > p { + line-height: 1.2rem !important; +} + .math.math-left { text-align: left; } @@ -64,6 +81,7 @@ table.right-align-vals td:not(:first-child) { padding: 0; color: black !important; font-size: 95%; + font-weight: normal; } .list-math-right .math { diff --git a/docs/source/gamma_index.rst b/docs/source/gamma_index.rst index 8451f3d..5712e99 100644 --- a/docs/source/gamma_index.rst +++ b/docs/source/gamma_index.rst @@ -18,8 +18,8 @@ Its acceptance criterion is expressed in percentages [%]. It is related to globa .. rst-class:: list -- global - a predetermined value, typically the maximum value in the reference image, -- local - value at the current point in the reference image. +- global -- a predetermined value, typically the maximum value in the reference image, +- local -- value at the current point in the reference image. If DD value at :math:`\vec{r_r}` point is at most the value of acceptance criterion (e.g. 3%, global), then this point passes the test. Otherwise it fails. diff --git a/docs/source/installation.rst b/docs/source/installation.rst index 11e4437..d6424a2 100644 --- a/docs/source/installation.rst +++ b/docs/source/installation.rst @@ -1,2 +1,222 @@ Installation ============ + +YAGIT requires C++ compiler that supports C++17 standard. +It also requires `CMake`_ (3.16 or newer). + +.. _CMake: https://cmake.org/ + +YAGIT uses these dependencies: + +.. rst-class:: list + +- `GDCM`_ -- used for reading DICOM files. +- `xsimd`_ -- used for vectorization. Used only when ``GAMMA_VERSION=SIMD`` or ``GAMMA_VERSION=THREADS_SIMD``. +- `GoogleTest`_ -- used for unit tests. Used only when ``BUILD_TESTING=ON``. + +.. _GDCM: https://github.com/malaterre/GDCM +.. _xsimd: https://github.com/xtensor-stack/xsimd +.. _GoogleTest: https://github.com/google/googletest + +You can build and install YAGIT using `setup script <#setup-script-install>`_ +or doing it `manually <#manual-install>`_. + + +Setup script installation +------------------------- + +To build YAGIT, simply run *setup.sh* or *setup.bat* script, depending on your operating system. + +On Linux, run: + +.. rst-class:: code +.. code-block:: + + ./setup.sh + +On Windows, run: + +.. rst-class:: code +.. code-block:: + + setup.bat + + +Note that, by default these scripts will only build the library but not install it. +To install it, configure the options appropriately in the script file. + +For now, the Windows script can only install dependencies using `Conan`_ package manager. + +.. _Conan: https://conan.io/ + + +Script options +~~~~~~~~~~~~~~ + +You can freely configure options that are in the script files. +Some of the options are the same as in the `CMake YAGIT options`_ section as they are simply passed to CMake. + +.. rst-class:: wrap-text +.. table:: + :align: center + + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | Option | Values | Default | Description | + +===============================+========================+=============+============================================+ + | ``BUILD_TYPE`` | ``Release``, ``Debug``,| ``Release`` | Build type used in the script | + | | ``RelWithDebInfo``, | | by CMake for single-target generators | + | | ``MinSizeRel`` | | (e.g. Makefile Generators) and | + | | | | by a compiler for multi-target generators | + | | | | (e.g. Visual Studio Generators). | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``BUILD_SHARED_LIBS`` | ``ON``, ``OFF`` | ``OFF`` | Equivalent to the CMake YAGIT option. | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``INSTALL_DEPENDENCIES`` | ``OFF``, ``LOCAL`` | ``LOCAL`` | Method of installing dependencies. | + | | ``GLOBAL``, ``CONAN`` | | Value ``OFF`` doesn't install any | + | | | | dependencies, and it assumes | + | | | | they are already installed system-wide. | + | | | | Value ``LOCAL`` installs dependencies | + | | | | locally to *build/deps* directory. | + | | | | Value ``GLOBAL`` installs dependencies | + | | | | system-wide. It requires admin privileges. | + | | | | Value ``CONAN`` installs dependencies | + | | | | using `Conan`_ package manager. | + | | | | It requires installed Conan. | + | | | | This option is only availble in *setup.sh*.| + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``GAMMA_VERSION`` | ``SEQUENTIAL``, | ``THREADS`` | Equivalent to the CMake YAGIT option. | + | | ``THREADS``, | | | + | | ``SIMD``, | | | + | | ``THREADS_SIMD`` | | | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``SIMD_EXTENSION`` | ``DEFAULT``, | ``DEFAULT`` | Equivalent to the CMake YAGIT option. | + | | ``SSE2``, ``SSE3``, | | | + | | ``SSSE3``, ``SSE4.1``, | | | + | | ``SSE4.2``, ``AVX``, | | | + | | ``AVX2``, ``AVX512``, | | | + | | ``NATIVE`` | | | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``ENABLE_FMA`` | ``ON``, ``OFF`` | ``OFF`` | Equivalent to the CMake YAGIT option. | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``BUILD_EXAMPLES`` | ``ON``, ``OFF`` | ``ON`` | Equivalent to the CMake YAGIT option. | + | | | | Additionally it runs examples. | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``BUILD_TESTING`` | ``ON``, ``OFF`` | ``OFF`` | Equivalent to the CMake YAGIT option. | + | | | | Additionally it runs unit tests. | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``BUILD_PERFORMANCE_TESTING`` | ``ON``, ``OFF`` | ``OFF`` | Equivalent to the CMake YAGIT option. | + | | | | Additionally it runs performance tests. | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``REF_IMG`` | --- | --- | Path to a reference image | + | | | | used in examples and performance tests. | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``EVAL_IMG`` | --- | --- | Path to an evaluated image | + | | | | used in examples and performance tests. | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``BUILD_DOCUMENTATION`` | ``ON``, ``OFF`` | ``OFF`` | Build documentation (*docs* directory). | + | | | | It requires `Doxygen`_, | + | | | | `Python`_ and libraries | + | | | | listed in *docs/requirements.txt*. | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``INSTALL`` | ``ON``, ``OFF`` | ``OFF`` | Install YAGIT library. | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``INSTALL_DIR`` | --- | ./yagit | Directory where YAGIT will be installed | + | | | | (only if ``INSTALL=ON``). | + | | | | If this is set to an empty string, | + | | | | then it will be installed system-wide. | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + + +.. _Doxygen: https://www.doxygen.nl/ +.. _Python: https://www.python.org/ + + +Manual installation +------------------- + +If you prefer to perform the installation manually without the script, +then follow the commands below to build and install YAGIT on Linux. +Before running them, ensure that you have installed the dependencies +(e.g. using a package manager or by building from source). + +.. code-block:: + + mkdir build && cd build + cmake .. -DCMAKE_BUILD_TYPE=Release + cmake --build . -j + sudo cmake --install . + + +If you don't have admin privileges or you want to install in a specific directory, then use this command: + +.. rst-class:: code +.. code-block:: + + cmake --install . --prefix + + +CMake YAGIT options +------------------- + +.. rst-class:: wrap-text +.. table:: + :align: center + + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | Option | Values | Default | Description | + +===============================+========================+=============+============================================+ + | ``BUILD_SHARED_LIBS`` | ``ON``, ``OFF`` | ``OFF`` | Build YAGIT as shared or static library. | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``BUILD_EXAMPLES`` | ``ON``, ``OFF`` | ``OFF`` | Build examples | + | | | | (*examples* directory). | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``BUILD_TESTING`` | ``ON``, ``OFF`` | ``OFF`` | Build unit tests | + | | | | (*tests/unit* directory). | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``BUILD_PERFORMANCE_TESTING`` | ``ON``, ``OFF`` | ``OFF`` | Build performance tests | + | | | | (*tests/performance* directory). | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``GAMMA_VERSION`` | ``SEQUENTIAL``, | ``THREADS`` | Implementation of an algorithm calculating | + | | ``THREADS``, | | the gamma index. | + | | ``SIMD``, | | | + | | ``THREADS_SIMD`` | | | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``SIMD_EXTENSION`` | ``DEFAULT``, | ``DEFAULT`` | SIMD instruction set extension. | + | | ``SSE2``, ``SSE3``, | | Works only when ``GAMMA_VERSION`` is | + | | ``SSSE3``, ``SSE4.1``, | | set to ``SIMD`` or ``THREADS_SIMD``. | + | | ``SSE4.2``, ``AVX``, | | Value ``DEFAULT`` adds no additional | + | | ``AVX2``, ``AVX512``, | | compilation flags. | + | | ``NATIVE`` | | Value ``NATIVE`` adds *-march=native* | + | | | | if compiler supports it. | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + | ``ENABLE_FMA`` | ``ON``, ``OFF`` | ``OFF`` | Enable fused multiply-add (FMA) | + | | | | when building YAGIT library. | + +-------------------------------+------------------------+-------------+--------------------------------------------+ + +To use these options, pass them to CMake during configuration using ``-DL7JaAtKj7f3DGJ+1rZelvNqbW*)2PwB@v6Ttti-=yB3V%>f@)gmzI%{h@V~5I^qU3sd zu4$S}zCG&NLdeXz-}(Ik7~En~-ga)~nVi{=t3mdQ3Gy;ZCig7XZmBqR$wW!@vpPMx z=R253f|)m;;XEufm1M?M#gg2f$x~bmu?s_eTiK_b#DLZ7pJ9xOK5+i@wi+ z)%XOaK+kVV`4~469A@Rqp6`7c{jf+A%bU3r1M7 z-U%V$-qjBjl4czS%@)Y7pHUsfcGD^=+YRsTzi;N^DT>tc*!3ge+UNGZhl6~eqb@0u 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zzM;wG1Q>ErlH=AgcBHw<6Z0Xh$*(QSMIW;A#pqTX@%9s!^rZVuv6OOtQ`a55Yrtqr zR1|Q=B3Wq?CI|4=XQ0uP5d`dHeN^dzx{wxA{}@*>#AS;Rcq%OWPd5}L#u!PX{`pN0fv|Wybb2&Q zLY$) bL%)STn7I@Qx%|(KPXBxEe}-*9fBpDBLP8Ue literal 0 HcmV?d00001 diff --git a/docs/source/index.rst b/docs/source/index.rst index f52f9aa..3a37af6 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -11,6 +11,7 @@ Yet Another Gamma Index Tool documentation parameters input_and_output_data data_representation + performance .. toctree:: diff --git a/docs/source/introduction.rst b/docs/source/introduction.rst index 6b77de3..1d5f8e6 100644 --- a/docs/source/introduction.rst +++ b/docs/source/introduction.rst @@ -23,115 +23,60 @@ Most important features of YAGIT are: - linear, bilinear, and trilinear interpolation of data. -Performance ------------ - -The performance of YAGIT has been compared with the performance of `FRED`_ and `PyMedPhys`_. -The gamma index module of FRED has been tested using the `FRED tools`_ library, -which calls functions of that module internally. - -.. _FRED: https://www.fred-mc.org/ -.. _FRED tools: https://github.com/jasqs/FREDtools -.. _PyMedPhys: https://github.com/pymedphys/pymedphys +Simple example +-------------- -Performance tests have been executed on a machine with an AMD Ryzen 7 5800H processor, -which has a clock speed of 3.2 GHz and features 8 cores and 16 threads. The machine has 16 GB of RAM DDR4 3200 MHz. +Below is a fragment of a program that calculates the 2D gamma index and saves the result to a file. -It has been tested on Windows 11 Home 64-bit (version 22H2) operating system with WSL2 and Ubuntu 22.04.2 LTS. -FRED's gamma index module requires Linux, so all tools have been tested on WSL2 to maintain an identical environment. +.. code-block:: c++ -This system contains gcc and g++ compilers in version 11.4.0 with glibc 2.35 and libstdc++ 3.4.30, CMake 3.22.1, -and Python 3.10.12. + // read a reference image and an evaluated image from DICOM files + const auto ref2d = yagit::DataReader::readRTDoseDicom("img_ref2d.dcm"); + const auto eval2d = yagit::DataReader::readRTDoseDicom("img_eval2d.dcm"); -Tested versions of tools are: + // set gamma index parameters + yagit::GammaParameters params; + params.ddThreshold = 3.0; // [%] + params.dtaThreshold = 3.0; // [mm] + params.normalization = yagit::GammaNormalization::Global; + params.globalNormDose = ref2d.max(); + params.doseCutoff = 0; + params.maxSearchDistance = 10; // [mm] + params.stepSize = params.dtaThreshold / 10; // [mm] -.. rst-class:: list + // calculate the 2D gamma index using the Wendling method + const auto gamma = yagit::gammaIndex2D(ref2d, eval2d, params); -- YAGIT built from 51d34ae commit (05.09.2023) using CMake tool in Release mode and g++ compiler, -- FRED tools 0.6.79 with libFredGI.so 4.2, -- PyMedPhys 0.39.3. - -Two 3D DICOM images have been used in the tests. -They have been generated using irradiation plans from DCPT LET-measurements 2022 [1]_. -The reference image has dimensions of 198x198x198, while the evaluated image has dimensions of 200x200x200. -They are very similar (GIPR ~ 99%). - - -.. rst-class:: center-headers right-align-vals -.. table:: - :align: center - - +------------+----------------------------------------------------------------+ - | | Average time [s] | - | +-------------------------+-------------------------+------------+ - | DD/DTA | YAGIT | FRED | PyMedPhys | - | +------------+------------+------------+------------+------------+ - | | 1 thread | 16 threads | 1 thread | 16 threads | 1 thread | - +============+============+============+============+============+============+ - | Wendling method -- 3D | - +------------+------------+------------+------------+------------+------------+ - | 3\%G/3mm | 3.022 | 0.363 | 7.991 | 1.078 | 200.822 | - +------------+------------+------------+------------+------------+------------+ - | 2\%G/2mm | 8.637 | 1.021 | 21.472 | 2.598 | 445.684 | - +------------+------------+------------+------------+------------+------------+ - | 3\%L/3mm | 3.534 | 0.427 | 9.145 | 1.238 | 224.542 | - +------------+------------+------------+------------+------------+------------+ - | 2\%L/2mm | 9.618 | 1.183 | 23.895 | 2.878 | 498.518 | - +------------+------------+------------+------------+------------+------------+ - -The table shows the comparison of calculation times between YAGIT, FRED, and PyMedPhys. -Other parameters: normalization dose = max value in the reference image, -dose cutoff = 5% of max value in the reference image, search radius = 3*DTA, step size = DTA/10. - -When using 16 threads, YAGIT and FRED speed up about 8 times. -It is 8, not 16, because the CPU on which it has been run has 8 cores. -16 threads have been used to achieve better speedup due to simultaneous multithreading (SMT). -PyMedPhys has been tested only with one thread because it doesn't support multithreaded gamma index. - - -.. figure:: _static/images/yfp_1thread.svg - :alt: Single-threaded gamma index using Wendling method - :align: center + // save the gamma index image to a MetaImage file + yagit::DataWriter::writeToMetaImage(gamma, "gamma2d.mha"); -The first image shows differences in computation times between single-threaded YAGIT, FRED, and PyMedPhys. -YAGIT is about 2.5 times faster than FRED and about 50--70 times faster than PyMedPhys. +The image below shows a 2D reference image, a 2D evaluated image, and their comparison. +The gamma index (3%G/3mm) has been calculated using the code above. +In addition, the difference between the evaluated image and the reference image is also shown. -.. figure:: _static/images/yf_16threads.svg - :alt: Multi-threaded gamma index using Wendling method +.. figure:: _static/images/introduction_example.jpg + :alt: Reference image, Evaluated image, Dose difference (eval - ref) image, Gamma index (3%G/3mm) image :align: center -The second image shows differences in computation times between multi-threaded YAGIT and FRED. -YAGIT is about 2--3 times faster than FRED. + +More examples with complete code are presented on the :doc:`examples ` subpage. -.. rst-class:: center-headers right-align-vals -.. table:: - :align: center +Performance +----------- - +------------+--------------------------------------+ - | | GIPR [%] | - | DD/DTA +------------+------------+------------+ - | | YAGIT | FRED | PyMedPhys | - +============+============+============+============+ - | Wendling method -- 3D | - +------------+------------+------------+------------+ - | 3\%G/3mm | 99.960 | 99.960 | 99.967 | - +------------+------------+------------+------------+ - | 2\%G/2mm | 99.144 | 99.145 | 99.232 | - +------------+------------+------------+------------+ - | 3\%L/3mm | 99.959 | 99.959 | 99.966 | - +------------+------------+------------+------------+ - | 2\%L/2mm | 99.049 | 99.050 | 99.025 | - +------------+------------+------------+------------+ +Calculating the 3D gamma index for large images can take a long time, +so an efficient implementation of the algorithm is crucial. +YAGIT is the fastest free library for calculating the gamma index. -In this table, it can be noticed that the values of GIPR in YAGIT and FRED are nearly identical. -However, PyMedPhys returns values that slightly differ from the other two tools. +.. figure:: _static/images/yf_16threads.svg + :alt: Multi-threaded gamma index using Wendling method + :align: center + A sample comparison of computation times for YAGIT and `FRED`_. + The gamma index has been calculated for two 3D images with dimensions of approximately 200x200x200 and GIPR ~ 99%. -References ----------- +.. _FRED: https://www.fred-mc.org/ -.. [1] N. Bassler, L. Grzanka, J. B. Christensen, J. Villads, H. Brkić, Y. Perrot, L. Pasariček, and M. Romero-Expósito, - “MC particle transport simulations for the 2022 LET-measurements at DCPT: v1.0.0”. - Zenodo, February 09, 2024. doi: 10.5281/zenodo.10641085. +More information about the performance of YAGIT is presented on the :doc:`performance ` subpage. diff --git a/docs/source/performance.rst b/docs/source/performance.rst new file mode 100644 index 0000000..fcf0090 --- /dev/null +++ b/docs/source/performance.rst @@ -0,0 +1,121 @@ +Performance +=========== + +The performance of YAGIT has been compared with the performance of `FRED`_ and `PyMedPhys`_. +The gamma index module of FRED has been tested using the `FRED tools`_ library, +which calls functions of that module internally. + +.. _FRED: https://www.fred-mc.org/ +.. _FRED tools: https://github.com/jasqs/FREDtools +.. _PyMedPhys: https://github.com/pymedphys/pymedphys + +Performance tests have been executed on a machine with an AMD Ryzen 7 5800H processor, +which has a clock speed of 3.2 GHz and features 8 cores and 16 threads. The machine has 16 GB of RAM DDR4 3200 MHz. + +It has been tested on Windows 11 Home 64-bit (version 22H2) operating system with WSL2 and Ubuntu 22.04.2 LTS. +FRED's gamma index module requires Linux, so all tools have been tested on WSL2 to maintain an identical environment. + +This system contains gcc and g++ compilers in version 11.4.0 with glibc 2.35 and libstdc++ 3.4.30, CMake 3.22.1, +and Python 3.10.12. + +Tested versions of tools are: + +.. rst-class:: list + +- YAGIT built from 51d34ae commit (05.09.2023) using CMake tool in Release mode and g++ compiler, +- FRED tools 0.6.79 with libFredGI.so 4.2, +- PyMedPhys 0.39.3. + +Two 3D DICOM images have been used in the tests. +They have been generated using irradiation plans from DCPT LET-measurements 2022 [1]_. +The reference image has been created in Eclipse TPS using an analytical dose calculation algorithm for proton therapy, +and the evaluated image has been created in Topas using Monte Carlo (MC) simulation. +The reference image has dimensions of 198x198x198, while the evaluated image has dimensions of 200x200x200. +The GIPR is quite high (~ 99%), which affects the computation time in the case of the tested Wendling method -- +in general, the higher the GIPR, the faster the gamma index is calculated. + + +Performance comparison +---------------------- + +.. rst-class:: center-headers right-align-vals +.. table:: + :align: center + + +------------+----------------------------------------------------------------+ + | | Average time [s] | + | +-------------------------+-------------------------+------------+ + | DD/DTA | YAGIT | FRED | PyMedPhys | + | +------------+------------+------------+------------+------------+ + | | 1 thread | 16 threads | 1 thread | 16 threads | 1 thread | + +============+============+============+============+============+============+ + | Wendling method -- 3D | + +------------+------------+------------+------------+------------+------------+ + | 3\%G/3mm | 3.022 | 0.363 | 7.991 | 1.078 | 200.822 | + +------------+------------+------------+------------+------------+------------+ + | 2\%G/2mm | 8.637 | 1.021 | 21.472 | 2.598 | 445.684 | + +------------+------------+------------+------------+------------+------------+ + | 3\%L/3mm | 3.534 | 0.427 | 9.145 | 1.238 | 224.542 | + +------------+------------+------------+------------+------------+------------+ + | 2\%L/2mm | 9.618 | 1.183 | 23.895 | 2.878 | 498.518 | + +------------+------------+------------+------------+------------+------------+ + +The table shows the comparison of calculation times between YAGIT, FRED, and PyMedPhys. +Other parameters: normalization dose = max value in the reference image, +dose cutoff = 5% of max value in the reference image, search radius = 3*DTA, step size = DTA/10. + +When using 16 threads, YAGIT and FRED speed up about 8 times. +It is 8, not 16, because the CPU on which it has been run has 8 cores. +16 threads have been used to achieve better speedup due to simultaneous multithreading (SMT). +PyMedPhys has been tested only with one thread because it doesn't support multithreaded gamma index. + + +.. figure:: _static/images/yfp_1thread.svg + :alt: Single-threaded gamma index using Wendling method + :align: center + +The first image shows differences in computation times between single-threaded YAGIT, FRED, and PyMedPhys. +YAGIT is about 2.5 times faster than FRED and about 50--70 times faster than PyMedPhys. + + +.. figure:: _static/images/yf_16threads.svg + :alt: Multi-threaded gamma index using Wendling method + :align: center + +The second image shows differences in computation times between multi-threaded YAGIT and FRED. +YAGIT is about 2--3 times faster than FRED. + + +GIPR comparison +---------------------- + +.. rst-class:: center-headers right-align-vals +.. table:: + :align: center + + +------------+--------------------------------------+ + | | GIPR [%] | + | DD/DTA +------------+------------+------------+ + | | YAGIT | FRED | PyMedPhys | + +============+============+============+============+ + | Wendling method -- 3D | + +------------+------------+------------+------------+ + | 3\%G/3mm | 99.960 | 99.960 | 99.967 | + +------------+------------+------------+------------+ + | 2\%G/2mm | 99.144 | 99.145 | 99.232 | + +------------+------------+------------+------------+ + | 3\%L/3mm | 99.959 | 99.959 | 99.966 | + +------------+------------+------------+------------+ + | 2\%L/2mm | 99.049 | 99.050 | 99.025 | + +------------+------------+------------+------------+ + +In this table, it can be noticed that the values of GIPR in YAGIT and FRED are nearly identical. +However, PyMedPhys returns values that slightly differ from the other two tools. + + +References +---------- + +.. [1] N. Bassler, L. Grzanka, J. B. Christensen, J. Villads, H. Brkić, Y. Perrot, L. Pasariček, and M. Romero-Expósito, + “MC particle transport simulations for the 2022 LET-measurements at DCPT: v1.0.0”. + Zenodo, February 09, 2024. doi: 10.5281/zenodo.10641085. From 03967e385462b24c0bed3d8397e63ea5a217d999 Mon Sep 17 00:00:00 2001 From: michal367 Date: Tue, 9 Apr 2024 20:21:20 +0200 Subject: [PATCH 23/25] add script for plotting introduction example --- docs/other/plot_introduction_example.py | 133 ++++++++++++++++++++++++ 1 file changed, 133 insertions(+) create mode 100644 docs/other/plot_introduction_example.py diff --git a/docs/other/plot_introduction_example.py b/docs/other/plot_introduction_example.py new file mode 100644 index 0000000..d4dce3d --- /dev/null +++ b/docs/other/plot_introduction_example.py @@ -0,0 +1,133 @@ +############################################################################################# +# Copyright (C) 2024 'Yet Another Gamma Index Tool' Developers. +# +# This file is part of 'Yet Another Gamma Index Tool'. +# +# 'Yet Another Gamma Index Tool' is free software: you can redistribute it and/or modify +# it under the terms of the GNU General Public License as published by +# the Free Software Foundation; either version 3 of the License, or +# (at your option) any later version. +# +# 'Yet Another Gamma Index Tool' is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +# GNU General Public License for more details. +# +# You should have received a copy of the GNU General Public License +# along with 'Yet Another Gamma Index Tool'. If not, see . +############################################################################################# + +# Python script for plotting image that is used on Introduction subpage of documentation. +# It consists of 4 images: a reference image, an evaluated image, a dose difference image, and a gamma index image. + +import matplotlib.pyplot as plt +import numpy as np +import SimpleITK as sitk +from matplotlib.colors import LinearSegmentedColormap +from mpl_toolkits.axes_grid1 import make_axes_locatable + + +# ============================================== +titles = ["Reference image", "Evaluated image", "Dose difference (eval - ref) image", "Gamma index (3%G/3mm) image"] +image_files = ["img_ref2d.mha", "img_eval2d.mha", "dd.mha", "gamma2d.mha"] +image_types = ["dose", "dose", "dd", "gamma"] +colorbar_labels = ["dose [Gy]", "dose [Gy]", "dose diff [Gy]", "gamma index"] + +# set vmin and vmax manually +dose_min, dose_max = 0, 2.8 +dd_min, dd_max = -0.5, 0.9 +gamma_min, gamma_max = 0, 1.6 # gamma_max >= 1.1 + + +# ============================================== + +def val_to_perc(val, min, max): + percent = (val - min) / (max - min) + if percent < 0 or percent > 1: + raise Exception("percent outside [0,1] range") + return percent + + +dose_colors = [(0, 0, 0), (0, 0, 0.6), (0, 0.5, 1), (0, 1, 1), + (0.5, 1, 0.5), (1, 1, 0), (1, 0.5, 0), (1, 0, 0), (0.5, 0, 0)] +dose_positions = np.linspace(0, 1, len(dose_colors)) +dose_cmap = LinearSegmentedColormap.from_list("dose_cmap", list(zip(dose_positions, dose_colors))) + +dd_colors = [(0, "#cc99ff"), + (val_to_perc(-0.25, dd_min, dd_max), "#8000ff"), + (val_to_perc(-0.05, dd_min, dd_max), "#4d0099"), + (val_to_perc(0, dd_min, dd_max), "black"), + (val_to_perc(0.05, dd_min, dd_max), "#004d99"), + (val_to_perc(0.25, dd_min, dd_max), "#0080ff"), + (1, "#cce6ff")] +dd_cmap = LinearSegmentedColormap.from_list("dd_cmap", dd_colors) + +gamma_colors = [(0, "#062e03"), + (val_to_perc(0.3, gamma_min, gamma_max), "green"), + (val_to_perc(0.6, gamma_min, gamma_max), "yellowgreen"), + (val_to_perc(0.999, gamma_min, gamma_max), "orange"), + (val_to_perc(1, gamma_min, gamma_max), "#ff0000"), + (1, "#660000")] +gamma_cmap = LinearSegmentedColormap.from_list("gamma_cmap", gamma_colors) + + +# ============================================== + +def read_metaimage_file(file_path): + image = sitk.ReadImage(file_path) + image_array = sitk.GetArrayFromImage(image)[0] # extract only the first frame + + size = image.GetSize() + origin = image.GetOrigin() + spacing = image.GetSpacing() + + return image_array, size, origin, spacing + +longest_title_len = len(max(titles, key=len)) + +def print_image_info(title, image_array, size, origin, spacing): + print(f"{title:<{longest_title_len + 2}}", + "size:", size[0:2], " origin:", origin[0:2], " spacing:", spacing[0:2], + " min:", image_array.min(), " max:", image_array.max()) + + +fig, axes = plt.subplots(2, 2, figsize=(9, 8)) + +for i, ax in enumerate(axes.flat): + image_array, size, origin, spacing = read_metaimage_file(image_files[i]) + print_image_info(titles[i], image_array, size, origin, spacing) + + if image_types[i] == "dose": im = ax.imshow(image_array, cmap=dose_cmap, vmin=dose_min, vmax=dose_max) + elif image_types[i] == "dd": im = ax.imshow(image_array, cmap=dd_cmap, vmin=dd_min, vmax=dd_max) + elif image_types[i] == "gamma": im = ax.imshow(image_array, cmap=gamma_cmap, vmin=gamma_min, vmax=gamma_max) + else: im = ax.imshow(image_array, cmap="grey") + + # ax.axis("off") + x_ticks = [i for i in range(0, size[0], 32)] + y_ticks = [i for i in range(0, size[1], 32)] + x_ticklabels = [int(origin[0] + i*spacing[0]) for i in x_ticks] + y_ticklabels = [int(origin[1] + i*spacing[1]) for i in y_ticks] + ax.set_xticks(x_ticks, labels=x_ticklabels, fontsize=9) + ax.set_yticks(y_ticks, labels=y_ticklabels, fontsize=9) + ax.xaxis.tick_top() + + ax.set_ylabel("y [mm]") + ax.set_xlabel("x [mm]") + ax.xaxis.set_label_position("top") + + ax.set_title(titles[i], y=-0.135) + + divider = make_axes_locatable(ax) + cax = divider.append_axes("right", size="5%", pad=0.1) + fig.colorbar(im, cax=cax, label=colorbar_labels[i]) + + +# ============================================== +plt.subplots_adjust(left=0.07, right=0.93, + bottom=0.09, top=0.91, + wspace=0.34, hspace=0.34) + +# plt.savefig("introduction_example.png", format="png") +plt.savefig("introduction_example.jpg", format="jpg") + +plt.show() From a2ad3738d5f835150b6eee124b5da0d02ab291c0 Mon Sep 17 00:00:00 2001 From: michal367 Date: Tue, 9 Apr 2024 21:02:06 +0200 Subject: [PATCH 24/25] doc fixes --- docs/source/algorithms.rst | 4 ++-- docs/source/gamma_index.rst | 13 ++++++------- docs/source/input_and_output_data.rst | 11 ++++++----- docs/source/parameters.rst | 6 +++--- docs/source/performance.rst | 2 +- 5 files changed, 18 insertions(+), 18 deletions(-) diff --git a/docs/source/algorithms.rst b/docs/source/algorithms.rst index 86d675d..b09ad68 100644 --- a/docs/source/algorithms.rst +++ b/docs/source/algorithms.rst @@ -65,11 +65,11 @@ for precise results. The values at points that do not exist in the evaluated image are determined on-the-fly using interpolation (e.g., bilinear for 2D and trilinear for 3D). -Some optimizations of on-the-fly interpolation can be achieved by resampling the evaluated image onto the grid +Some optimizations of the on-the-fly interpolation can be achieved by resampling the evaluated image onto the grid of the reference image before initiating gamma index calculations. However, YAGIT doesn't perform this step due to two reasons that can lead to less accurate results. Firstly, this approach involves double interpolation -- -first during the resampling process and second during on-the-fly interpolation. +first during the resampling process and second during the on-the-fly interpolation. The second interpolation uses interpolated points from the first interpolation, which can result in less accurate results. Another reason is the fact that the evaluated image we start with can have a denser grid than the reference image, diff --git a/docs/source/gamma_index.rst b/docs/source/gamma_index.rst index 6146944..acd2dbb 100644 --- a/docs/source/gamma_index.rst +++ b/docs/source/gamma_index.rst @@ -24,8 +24,8 @@ Its acceptance criterion is expressed in percentages [%]. It is relative to glob If the DD value at :math:`\vec{r_r}` point is less than or equal to the value of the acceptance criterion (e.g., 3%, global), then this point passes the test. Otherwise, it fails. -The drawback of this test is that it struggles with high gradient regions, as small shifts in the spatial -distribution of radiation doses can result in large DD values. +The drawback of this test is that it struggles with high-gradient regions, as small shifts in the spatial +distribution of radiation dose can result in large DD values. Distance To Agreement @@ -43,15 +43,15 @@ Its acceptance criterion is expressed in millimeters [mm]. If the DTA value at :math:`\vec{r_r}` point is less than or equal to the value of the acceptance criterion (e.g., 3 mm), then this point passes the test. Otherwise, it fails. -The drawback of this method is that it encounters difficulties in low gradient areas, -where minor dose misalignments may require a large search radius (large DTA value). +The drawback of this method is that it encounters difficulties in low-gradient areas, +where minor dose misalignments may require a large search radius, resulting in a large DTA value. Gamma function and gamma index ------------------------------ To overcome the disadvantages of DD and DTA, the gamma index was developed. -Before calculating it, it is necessary to first determine the gamma function, which combines DD and DTA. +First, it is necessary to calculate the gamma function, which combines DD and DTA. In the case of the DTA component, only the distance is calculated without taking into account the condition of equal doses. @@ -83,8 +83,7 @@ that is, how many gamma index values are less than or equal to 1. .. math:: GIPR = \frac{| \{\gamma(\vec{r_r}) \le 1\} |}{| \{\gamma(\vec{r_r})\} |} -When this value is sufficiently high (e.g., 90%), it can be considered that -the two compared images are sufficiently similar to each other. +If this value is sufficiently high (e.g., at least 90%), the evaluated image is acceptable. Flow diagram diff --git a/docs/source/input_and_output_data.rst b/docs/source/input_and_output_data.rst index 9f78040..1105030 100644 --- a/docs/source/input_and_output_data.rst +++ b/docs/source/input_and_output_data.rst @@ -9,11 +9,12 @@ Input data ---------- The input data for the gamma index calculation algorithm consists of two-dimensional or three-dimensional images -containing the distribution of radiation dose. -Two images are needed for comparison: the reference image (also known as measured) -and the evaluated image (also known as calculated or planned). -Typically, the reference image is obtained from measurements of the actual radiation dose by appropriate detectors. -Meanwhile, the evaluated image is usually the image generated by the Treatment Planning System (TPS). +containing a spatial distribution of radiation dose. +Two images are needed for comparison: a reference image and an evaluated image. +Typically, the reference image is a measured image, +which is obtained from measurements of an actual radiation dose by appropriate detectors. +Meanwhile, the evaluated image is usually a calculated/planned image, +which is an image generated by a treatment planning system (TPS). .. figure:: _static/images/reference_image_example.png :alt: Example of a reference image diff --git a/docs/source/parameters.rst b/docs/source/parameters.rst index 8715c03..d01b900 100644 --- a/docs/source/parameters.rst +++ b/docs/source/parameters.rst @@ -25,10 +25,10 @@ Frequently used parameters in radiotherapy are values within the range of 1--3% with global normalization and 1--3 mm for the acceptance criterion DTA. These parameters are shortened, e.g., 3%G/3mm (3% DD criterion, global normalization, 3 mm DTA criterion). -In YAGIT, in the case of local normalization, when the dose value at the current reference point is 0, +In YAGIT, in the case of local normalization, if the dose value at the current reference point is 0, that point is skipped to avoid division by zero. -Similarly, when a reference point has a value below the dose cutoff value, such a point is also skipped. -In both cases, the gamma index value will be set to NaN. +Similarly, if a reference point has a value below the dose cutoff value, such a point is also skipped. +In both cases, the gamma index value is set to NaN. When calculating GIPR, NaN values are not taken into account in either the numerator or the denominator. diff --git a/docs/source/performance.rst b/docs/source/performance.rst index fcf0090..af06075 100644 --- a/docs/source/performance.rst +++ b/docs/source/performance.rst @@ -29,7 +29,7 @@ Tested versions of tools are: Two 3D DICOM images have been used in the tests. They have been generated using irradiation plans from DCPT LET-measurements 2022 [1]_. The reference image has been created in Eclipse TPS using an analytical dose calculation algorithm for proton therapy, -and the evaluated image has been created in Topas using Monte Carlo (MC) simulation. +and the evaluated image has been created in TOPAS using Monte Carlo (MC) simulation. The reference image has dimensions of 198x198x198, while the evaluated image has dimensions of 200x200x200. The GIPR is quite high (~ 99%), which affects the computation time in the case of the tested Wendling method -- in general, the higher the GIPR, the faster the gamma index is calculated. From b4953f20019b7c7cf5a930ae985756dc9ede1e70 Mon Sep 17 00:00:00 2001 From: michal367 Date: Tue, 9 Apr 2024 21:13:09 +0200 Subject: [PATCH 25/25] fix typo --- .github/workflows/documentation.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/documentation.yml b/.github/workflows/documentation.yml index d75318f..1bd65c2 100644 --- a/.github/workflows/documentation.yml +++ b/.github/workflows/documentation.yml @@ -5,7 +5,7 @@ on: types: [ published ] jobs: - documenation: + documentation: runs-on: ubuntu-latest steps: