Better flux and pdf with line numbers

ohbm · Oct 9, 2023 · cedeb8b · cedeb8b
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Showing 3 changed files with 23 additions and 5 deletions.
diff --git a/compiled/main_linenum.pdf b/compiled/main_linenum.pdf
diff --git a/main.tex b/main.tex
@@ -20,7 +20,16 @@
 % \usepackage[pdftex]{graphicx}
 \usepackage{xcolor} % Required for specifying colors by name
 \usepackage{subcaption}
+\usepackage{placeins}
 
+\let\Oldsection\section
+\renewcommand{\section}{\FloatBarrier\Oldsection}
+
+\let\Oldsubsection\subsection
+\renewcommand{\subsection}{\FloatBarrier\Oldsubsection}
+
+% \let\Oldsubsubsection\subsubsection
+% \renewcommand{\subsubsection}{\FloatBarrier\Oldsubsubsection}
 %--------------------------------------------
 % Hyperlinks
 %--------------------------------------------
@@ -69,6 +78,9 @@
 \newcommand{\authors}[1]{\emph{\footnotesize #1} \\}
 \newcommand{\affiliations}[1]{{\scriptsize #1} \\}
 
+% \usepackage{lineno}
+% \linenumbers
+
 
 \title{Proceedings of the OHBM Brainhack 2022}
 %\subtitle{subtitle}
@@ -323,6 +335,9 @@ \section*{Introduction}
 
 After a quick explanation of each main contribution of the core team, the next pages are dedicated to the summaries of the projects that were developed during the four days of hacking.
 
+\vfill\eject
+\columnbreak
+
 \section{Hacktrack}
 
 \authors{Dorota Jarecka, %
@@ -471,6 +486,9 @@ \section{Project Reports}
 \subfile{summaries/flux.tex}
 \subfile{summaries/hyppomriqc.tex}
 \subfile{summaries/metadata-community.tex}
+\vfill\eject
+\columnbreak
+
 \subfile{summaries/narps-open-pipelines.tex}
 \subfile{summaries/neurocausal.tex}
 \subfile{summaries/neuroscout.tex}

diff --git a/summaries/hyppomriqc.tex b/summaries/hyppomriqc.tex
@@ -18,18 +18,18 @@ \subsubsection{Method}
 We ran the three pipelines on T1 images from 15 subjects from the Prevent-AD Alzheimer’s dataset \parencite{tremblay2021open}, composed of cognitively healthy participants between the ages of 55-88 years old that are at risk of developing Alzheimer's Disease. 
 We ran MRIQC \parencite{esteban2017mriqc} - a tool for performing automatic quality control and extracting quality measures from MRI scans - on the 15 T1 scans and obtained Image Quality Metrics (IQMs) from them. We then found the correlations between the IQMs and the pairwise inter-pipeline discrepancy of the left hippocampal volumes for each T1 scan.
 
-\subsubsection{Results}
-
-We found that for The FSL-FreeSurfer and FSL-ASHs discrepancies, MRIQC’s EFC measure produced the highest correlation, of 0.69 and 0.64, respectively. The EFC “uses the Shannon entropy of voxel intensities as an indication of ghosting and blurring induced by head motion” \parencite{MRIQCdoc}. No such correlations were found for the ASHS-FreeSurfer discrepancies. \Cref{fig:MRIQC-fig} shows a scatter plot of the discrepancies in left hippocampal volume and EFC IQM for each pipeline pairing. The preliminary results suggest that FSL’s hippocampal segmentation may be sensitive to head motion in T1 scans, leading to larger result discrepancies, but we require larger sample sizes to make meaningful conclusions. The code for our project can be found on GitHub at \href{https://github.com/jacobsanz97/Pipeline-Discrepancy-Exploration}{this link}. 
-
-\begin{figure}
+\begin{figure}[!h]
 	\centering
 	\includegraphics[width=0.4\textwidth]{MRIQC-fig.png}
 	\caption{Plots showing the association between left hippocampal volume discrepancies and MRIQC’s EFC quality measure for each of the pipeline pairings.}
 	% Add a label to reference in text. Make it specific!
 	\label{fig:MRIQC-fig}
 \end{figure}
 
+\subsubsection{Results}
+
+We found that for The FSL-FreeSurfer and FSL-ASHs discrepancies, MRIQC’s EFC measure produced the highest correlation, of 0.69 and 0.64, respectively. The EFC “uses the Shannon entropy of voxel intensities as an indication of ghosting and blurring induced by head motion” \parencite{MRIQCdoc}. No such correlations were found for the ASHS-FreeSurfer discrepancies. \Cref{fig:MRIQC-fig} shows a scatter plot of the discrepancies in left hippocampal volume and EFC IQM for each pipeline pairing. The preliminary results suggest that FSL’s hippocampal segmentation may be sensitive to head motion in T1 scans, leading to larger result discrepancies, but we require larger sample sizes to make meaningful conclusions. The code for our project can be found on GitHub at \href{https://github.com/jacobsanz97/Pipeline-Discrepancy-Exploration}{this link}. 
+
 \subsubsection{Conclusion and Next Steps}
 
 In this project, we investigated the correlation between MRIQC’s IQMs and discrepancies in left hippocampal volume derived from three common neuroimaging pipelines on 15 subjects from the Prevent-AD study dataset. While our preliminary results indicate image ghosting and blurring induced by head motion may play a role in inter-pipeline result discrepancies, the next steps of the project will consist of computing the correlations on the full 308 subjects of the Prevent-AD dataset to investigate whether they persist with the full sample.