merge master into v2

README.md

@@ -7,7 +7,7 @@ Overview of [improvements](resources/improvements_in_v2.md) in TotalSegmentator
 ![Alt text](resources/imgs/overview_classes.png)
 
 Created by the department of [Research and Analysis at University Hospital Basel](https://www.unispital-basel.ch/en/radiologie-nuklearmedizin/forschung-radiologie-nuklearmedizin).  
-If you use it please cite our paper: [https://arxiv.org/abs/2208.05868](https://arxiv.org/abs/2208.05868). Please also cite [nnUNet](https://github.com/MIC-DKFZ/nnUNet) since TotalSegmentator is heavily based on it.
+If you use it please cite our [Radiology AI paper](https://pubs.rsna.org/doi/10.1148/ryai.230024). Please also cite [nnUNet](https://github.com/MIC-DKFZ/nnUNet) since TotalSegmentator is heavily based on it.
 
 
 ### Installation
@@ -158,10 +158,10 @@ TotalSegmentator (starting in v1.5.4) sends anonymous usage statistics to help u
 
 
 ### Reference 
-For more details see this paper [https://arxiv.org/abs/2208.05868](https://arxiv.org/abs/2208.05868).
+For more details see our [Radiology AI paper](https://pubs.rsna.org/doi/10.1148/ryai.230024) ([freely available preprint](https://arxiv.org/abs/2208.05868)).
 If you use this tool please cite it as follows
 ```
-Wasserthal J., Meyer M., Breit H., Cyriac J., Yang S., Segeroth M. TotalSegmentator: robust segmentation of 104 anatomical structures in CT images, 2022. URL: https://arxiv.org/abs/2208.05868.  arXiv: 2208.05868
+Wasserthal, J., Breit, H.-C., Meyer, M.T., Pradella, M., Hinck, D., Sauter, A.W., Heye, T., Boll, D., Cyriac, J., Yang, S., Bach, M., Segeroth, M., 2023. TotalSegmentator: Robust Segmentation of 104 Anatomic Structures in CT Images. Radiology: Artificial Intelligence. https://doi.org/10.1148/ryai.230024
 ```
 Please also cite [nnUNet](https://github.com/MIC-DKFZ/nnUNet) since TotalSegmentator is heavily based on it.  
 Moreover, we would really appreciate if you let us know what you are using this tool for. You can also tell us what classes we should add in future releases. You can do so [here](https://github.com/wasserth/TotalSegmentator/issues/1).

bin/TotalSegmentator

@@ -10,7 +10,7 @@ from totalsegmentator.python_api import totalsegmentator
 
 def main():
     parser = argparse.ArgumentParser(description="Segment 104 anatomical structures in CT images.",
-                                     epilog="Written by Jakob Wasserthal. If you use this tool please cite https://arxiv.org/abs/2208.05868")
+                                     epilog="Written by Jakob Wasserthal. If you use this tool please cite https://pubs.rsna.org/doi/10.1148/ryai.230024")
 
     parser.add_argument("-i", metavar="filepath", dest="input",
                         help="CT nifti image or folder of dicom slices", 

bin/crop_to_body

@@ -17,7 +17,7 @@ from totalsegmentator.cropping import crop_to_mask, undo_crop
 
 def main():
     parser = argparse.ArgumentParser(description="Crop input image to body.",
-                                     epilog="Written by Jakob Wasserthal. If you use this tool please cite https://arxiv.org/abs/2208.05868")
+                                     epilog="Written by Jakob Wasserthal. If you use this tool please cite https://pubs.rsna.org/doi/10.1148/ryai.230024")
 
     parser.add_argument("-i", metavar="filepath", dest="input",
                         help="CT nifti image", 

bin/totalseg_combine_masks

@@ -21,7 +21,7 @@ if __name__ == "__main__":
     totalseg_combine_masks -i totalsegmentator_output_dir -o combined_mask.nii.gz -m lung
     """
     parser = argparse.ArgumentParser(description="Combine masks.",
-                                     epilog="Written by Jakob Wasserthal. If you use this tool please cite https://arxiv.org/abs/2208.05868")
+                                     epilog="Written by Jakob Wasserthal. If you use this tool please cite https://pubs.rsna.org/doi/10.1148/ryai.230024")
 
     parser.add_argument("-i", metavar="directory", dest="mask_dir",
                         help="TotalSegmentator output directory containing all the masks", 

bin/totalseg_download_weights

@@ -5,7 +5,7 @@ from pathlib import Path
 import argparse
 
 from totalsegmentator.libs import download_pretrained_weights
-
+from totalsegmentator.config import setup_totalseg
 
 if __name__ == "__main__":
     """
@@ -33,6 +33,8 @@ if __name__ == "__main__":
         "liver_vessels": [8]
     }
 
+    setup_totalseg()
+
     for task_id in task_to_id[args.task]:
         print(f"Processing {task_id}...")
         download_pretrained_weights(task_id)

bin/totalseg_setup_manually

@@ -18,7 +18,7 @@ if __name__ == "__main__":
     totalseg_setup_manually -id totalseg_12345678
     """
     parser = argparse.ArgumentParser(description="Combine masks.",
-                                     epilog="Written by Jakob Wasserthal. If you use this tool please cite https://arxiv.org/abs/2208.05868")
+                                     epilog="Written by Jakob Wasserthal. If you use this tool please cite https://pubs.rsna.org/doi/10.1148/ryai.230024")
 
     parser.add_argument("-id", "--totalseg_id", type=str, help="totalseg_id. Must start with totalseg_.",
                         required=True)

totalsegmentator/config.py

@@ -88,7 +88,7 @@ def get_version():
 
 
 def send_usage_stats(config, params):
-    if config["send_usage_stats"]:
+    if config is not None and config["send_usage_stats"]:
 
         params["roi_subset"] = "" if params["roi_subset"] is None else "-".join(params["roi_subset"])
 

totalsegmentator/python_api.py

@@ -51,7 +51,7 @@ def totalsegmentator(input, output, ml=False, nr_thr_resamp=1, nr_thr_saving=6,
     nora_tag = "None" if nora_tag is None else nora_tag
 
     if not quiet: 
-        print("\nIf you use this tool please cite: https://doi.org/10.48550/arXiv.2208.05868\n")
+        print("\nIf you use this tool please cite: https://pubs.rsna.org/doi/10.1148/ryai.230024\n")
 
     if not torch.cuda.is_available():
         print("No GPU detected. Running on CPU. This can be very slow. The '--fast' option can help to some extend.")