Implementation of the MICCAI 2019 Paper "Matwo-CapsNet: a Multi-Label Semantic Segmentation Capsules Network".
| Method | Parameters | Loss | Left lung | Right lung | Left clavicule | Right clavicule | Heart |
|---|---|---|---|---|---|---|---|
| U-Net | 42K | Softmax | 97.36 | 97.87 | 90.87 | 90.64 | 94.49 |
| SegCaps | 2,129K | weighted Softmax | 21.18 | 35.79 | 4.49 | 2.93 | 32.83 |
| SegCaps | 2,129K | weighted Spread loss | 30.74 | 0 | 0.06 | 0 | 23.23 |
| MatVec-CapsNet O_r | 43K | Spread loss | 95.57 | 96.43 | 82.89 | 82.56 | 92.37 |
| MatVec-CapsNet D_r | 43K | Spread loss | 96.60 | 97.15 | 86.41 | 86.38 | 93.42 |
| Matwo-CapsNet | 43K | Spread loss | 97.01 | 97.45 | 88.32 | 87.82 | 94.37 |
Download the files from :
Extract the archives in ./Dataset before running ./Dataset/dataset_preprocessing.py
Run main_train_and_test.py to train the network. You can run any of the paper experiment by simply uncommenting the different settings at the end of the script.
In order to train and test on other datasets, modify the dataset.py file. See the example files and documentation for the specific file formats. Set the parameter save_debug_images = True in order to see, if the network input images are reasonable.
If you use this code for your research, please cite our Paper:
@inproceedings{Bonheur2019,
title = {Matwo-CapsNet: a Multi-Label Semantic Segmentation Capsules Network},
author = {Bonheur, Savinien and {\v{S}}tern, Darko and Payer, Christian and Pienn, Michael and Olschewski, Horst and Urschler, Martin},
booktitle = {International Conference on Medical Image Computing and Computer-Assisted Intervention},
doi = {978-3-030-32254-0_74},
pages = {664-672},
year = {2019},
}
This code make use of the following projects:
@inproceedings{Payer2018a,
title = {Multi-label Whole Heart Segmentation Using {CNNs} and Anatomical Label Configurations},
author = {Payer, Christian and {\v{S}}tern, Darko and Bischof, Horst and Urschler, Martin},
booktitle = {Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges. STACOM 2017},
doi = {10.1007/978-3-319-75541-0_20},
pages = {190--198},
year = {2018},
}
@article{lalonde2018capsules,
title={Capsules for Object Segmentation},
author={LaLonde, Rodney and Bagci, Ulas},
journal={arXiv preprint arXiv:1804.04241},
year={2018}
}
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