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	title = {A {Simple} {Framework} for {Contrastive} {Learning} of {Visual} {Representations}},
	urldate = {2023-11-08},
	booktitle = {International {Conference} on {Machine} {Learning}},
	author = {Chen, Ting and Kornblith, Simon and Norouzi, Mohammad and Hinton, Geoffrey},
	year = {2020},
	pages = {1597--1607},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/AGBRAUGY/Chen et al. - 2020 - A Simple Framework for Contrastive Learning of Vis.pdf:application/pdf;Supplementary PDF:/Users/benjamin/Zotero/storage/G3FB3SRX/Chen et al. - 2020 - A Simple Framework for Contrastive Learning of Vis.pdf:application/pdf},
}

@inproceedings{ronneberger_u-net_2015,
	title = {U-{Net}: {Convolutional} {Networks} for {Biomedical} {Image} {Segmentation}},
	booktitle = {Medical {Image} {Computing} and {Computer}-{Assisted} {Intervention}},
	author = {Ronneberger, Olaf and Fischer, Philipp and Brox, Thomas},
	year = {2015},
	keywords = {Convolutional Layer, Data Augmentation, Deep Network, Ground Truth Segmentation, Training Image},
	pages = {234--241},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/SSV9QNJ3/Ronneberger et al. - 2015 - U-Net Convolutional Networks for Biomedical Image.pdf:application/pdf},
}

@misc{kingma_adam_2014,
	title = {Adam: {A} {Method} for {Stochastic} {Optimization}},
	author = {Kingma, Diederik and Ba, Jimmy},
	year = {2014},
	note = {arXiv:1412.6980},
	keywords = {Computer Science - Machine Learning},
	annote = {Comment: Published as a conference paper at the 3rd International Conference for Learning Representations, San Diego, 2015},
	file = {arXiv Fulltext PDF:/Users/benjamin/Zotero/storage/KYB95MYJ/Kingma and Ba - 2017 - Adam A Method for Stochastic Optimization.pdf:application/pdf;arXiv.org Snapshot:/Users/benjamin/Zotero/storage/MNQJHAMD/1412.html:text/html},
}

@article{billot_synthseg_2023,
	title = {{SynthSeg}: {Segmentation} of brain {MRI} scans of any contrast and resolution without retraining},
	volume = {86},
	journal = {Medical Image Analysis},
	author = {Billot, Benjamin and Greve, Douglas and Puonti, Oula and Thielscher, Axel and Van Leemput, Koen and Fischl, Bruce and Dalca, Adrian and Iglesias, Juan Eugenio},
	year = {2023},
	keywords = {CNN, Contrast and resolution invariance, Domain randomisation, Segmentation},
	pages = {102789},
	file = {Accepted Version:/Users/benjamin/Zotero/storage/9GFJ4UAD/Billot et al. - 2023 - SynthSeg Segmentation of brain MRI scans of any c.pdf:application/pdf;ScienceDirect Snapshot:/Users/benjamin/Zotero/storage/MMD6NEGA/S1361841523000506.html:text/html},
}

@inproceedings{huang_multi-organ_2020,
	title = {Multi-organ {Segmentation} via {Co}-training {Weight}-{Averaged} {Models} from {Few}-{Organ} {Datasets}},
	booktitle = {Medical {Image} {Computing} and {Computer} {Assisted} {Intervention}},
	author = {Huang, Rui and Zheng, Yuanjie and Hu, Zhiqiang and Zhang, Shaoting and Li, Hongsheng},
	year = {2020},
	keywords = {Co-training, Few-organ datasets, Multi-organ segmentation},
	pages = {146--155},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/2AM7HALZ/Huang et al. - 2020 - Multi-organ Segmentation via Co-training Weight-Av.pdf:application/pdf},
}

@article{hongdong_multi-scale_2022,
	title = {Multi-scale organs image segmentation method improved by squeeze-and-attention based on partially supervised learning},
	volume = {17},
	number = {6},
	journal = {International Journal of Computer Assisted Radiology and Surgery},
	author = {Hongdong, Mao and Guogang, Cao and Shu, Zhang and Shunkun, Liu and Deqing, Kong and Sicheng, Li and Zeyu, Peng and Yan, Wu and Ying, Chen and Cuixia, Dai},
	year = {2022},
	keywords = {Image segmentation, Multi-scale organs, Partially supervised learning, Squeeze-and-attention},
	pages = {1135--1142},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/294NXG3N/Hongdong et al. - 2022 - Multi-scale organs image segmentation method impro.pdf:application/pdf},
}

@inproceedings{zhou_prior-aware_2019,
	title = {Prior-{Aware} {Neural} {Network} for {Partially}-{Supervised} {Multi}-{Organ} {Segmentation}},
	booktitle = {International {Conference} on {Computer} {Vision}},
	author = {Zhou, Yuyin and Li, Zhe and Bai, Song and Wang, Chong and Chen, Xinlei and Han, Mei and Fishman, Elliot and Yuille, Alan},
	year = {2019},
	pages = {10672--10681},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/38JBHB42/Zhou et al. - 2019 - Prior-Aware Neural Network for Partially-Supervise.pdf:application/pdf},
}

@inproceedings{zhang_dodnet_2021,
	title = {{DoDNet}: {Learning} to {Segment} {Multi}-{Organ} and {Tumors} from {Multiple} {Partially} {Labeled} {Datasets}},
	booktitle = {Conference on {Computer} {Vision} and {Pattern} {Recognition}},
	author = {Zhang, Jianpeng and Xie, Yutong and Xia, Yong and Shen, Chunhua},
	month = jun,
	year = {2021},
	keywords = {Head, Image segmentation, Annotations, Encoding, Labeling, Task analysis, Three-dimensional displays},
	pages = {1195--1204},
	file = {IEEE Xplore Abstract Record:/Users/benjamin/Zotero/storage/4VF4D79C/9578768.html:text/html;Submitted Version:/Users/benjamin/Zotero/storage/8WH7XPQW/Zhang et al. - 2021 - DoDNet Learning to Segment Multi-Organ and Tumors.pdf:application/pdf},
}

@article{atzeni_deep_2022,
	title = {Deep active learning for suggestive segmentation of biomedical image stacks via optimisation of {Dice} scores and traced boundary length},
	volume = {81},
	journal = {Medical Image Analysis},
	author = {Atzeni, Alessia and Peter, Loic and Robinson, Eleanor and Blackburn, Emily and Althonayan, Juri and Alexander, Daniel and Iglesias, Juan Eugenio},
	year = {2022},
	keywords = {Deep learning, Segmentation, Active learning, Histology, Partial annotation},
	file = {Full Text:/Users/benjamin/Zotero/storage/N9K7CFUQ/Atzeni et al. - 2022 - Deep active learning for suggestive segmentation o.pdf:application/pdf;ScienceDirect Snapshot:/Users/benjamin/Zotero/storage/A5R7ITQ7/S1361841522001967.html:text/html},
}

@inproceedings{filbrandt_learning_2021,
	title = {Learning from {Partially} {Overlapping} {Labels}: {Image} {Segmentation} {Under} {Annotation} {Shift}},
	booktitle = {Domain {Adaptation} and {Transfer} {Learning} {Workshop}},
	author = {Filbrandt, Gregory and Kamnitsas, Konstantinos and Bernstein, David and Taylor, Alexandra and Glocker, Ben},
	year = {2021},
	pages = {23--32},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/6AYXJJCV/Filbrandt et al. - 2021 - Learning from Partially Overlapping Labels Image .pdf:application/pdf},
}

@article{dorent_learning_2021,
	title = {Learning joint segmentation of tissues and brain lesions from task-specific hetero-modal domain-shifted datasets},
	volume = {67},
	journal = {Medical Image Analysis},
	author = {Dorent, Reuben and Booth, Thomas and Li, Wenqi and Sudre, Carole and Kafiabadi, Sina and Cardoso, Jorge and Ourselin, Sebastien and Vercauteren, Tom},
	year = {2021},
	keywords = {Domain adaptation, Joint learning, Multi-Modal, Multi-Task learning},
	file = {Full Text:/Users/benjamin/Zotero/storage/URRVNRPU/Dorent et al. - 2021 - Learning joint segmentation of tissues and brain l.pdf:application/pdf;ScienceDirect Snapshot:/Users/benjamin/Zotero/storage/HALJT5CS/S1361841520302267.html:text/html},
}

@inproceedings{fidon_label-set_2021,
	title = {Label-{Set} {Loss} {Functions} for {Partial} {Supervision}: {Application} to {Fetal} {Brain} {3D} {MRI} {Parcellation}},
	booktitle = {Medical {Image} {Computing} and {Computer} {Assisted} {Intervention}},
	author = {Fidon, Lucas and Aertsen, Michael and Emam, Doaa and Mufti, Nada and Guffens, Frédéric and Deprest, Thomas and Demaerel, Philippe and David, Anna and Melbourne, Andrew and Ourselin, Sébastien and Deprest, Jan and Vercauteren, Tom},
	year = {2021},
	pages = {647--657},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/BIZGMTZD/Fidon et al. - 2021 - Label-Set Loss Functions for Partial Supervision .pdf:application/pdf},
}

@inproceedings{roulet_joint_2019,
	title = {Joint {Learning} of {Brain} {Lesion} and {Anatomy} {Segmentation} from {Heterogeneous} {Datasets}},
	booktitle = {Medical {Imaging} with {Deep} {Learning}},
	author = {Roulet, Nicolas and Slezak, Diego Fernandez and Ferrante, Enzo},
	year = {2019},
	pages = {401--413},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/U7K7HM4B/Roulet et al. - 2019 - Joint Learning of Brain Lesion and Anatomy Segment.pdf:application/pdf},
}

@inproceedings{ulrich_multitalent_2023,
	title = {{MultiTalent}: {A} {Multi}-dataset {Approach} to {Medical} {Image} {Segmentation}},
	booktitle = {Medical {Image} {Computing} and {Computer} {Assisted} {Intervention}},
	author = {Ulrich, Constantin and Isensee, Fabian and Wald, Tassilo and Zenk, Maximilian and Baumgartner, Michael and Maier-Hein, Klaus},
	year = {2023},
	keywords = {foundation model, Medical image segmentation, multitask learning, partially labeled datasets, transfer learning},
	pages = {648--658},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/LJ3JBGVH/Ulrich et al. - 2023 - MultiTalent A Multi-dataset Approach to Medical I.pdf:application/pdf},
}

@inproceedings{liu_clip-driven_2023,
	title = {{CLIP}-{Driven} {Universal} {Model} for {Organ} {Segmentation} and {Tumor} {Detection}},
	booktitle = {International {Conference} on {Computer} {Vision}},
	author = {Liu, Jie and Zhang, Yixiao and Chen, Jie-Neng and Xiao, Junfei and Lu, Yongyi and A Landman, Bennett and Yuan, Yixuan and Yuille, Alan and Tang, Yucheng and Zhou, Zongwei},
	year = {2023},
	pages = {21152--21164},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/Z3SEHS83/Liu et al. - 2023 - CLIP-Driven Universal Model for Organ Segmentation.pdf:application/pdf},
}

@misc{li_multi-organ_2023,
	title = {Multi-organ segmentation: a progressive exploration of learning paradigms under scarce annotation},
	author = {Li, Shiman and Wang, Haoran and Meng, Yucong and Zhang, Chenxi and Song, Zhijian},
	year = {2023},
	note = {arXiv:2302.03296},
	keywords = {Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing},
	annote = {Comment: 23 pages, 4 figures, 5 tables},
	file = {arXiv Fulltext PDF:/Users/benjamin/Zotero/storage/NSI2KQN6/Li et al. - 2023 - Multi-organ segmentation a progressive exploratio.pdf:application/pdf;arXiv.org Snapshot:/Users/benjamin/Zotero/storage/M7RMSI7P/2302.html:text/html},
}

@inproceedings{wang_automatic_2018,
	title = {Automatic {Brain} {Tumor} {Segmentation} {Using} {Cascaded} {Anisotropic} {Convolutional} {Neural} {Networks}},
	booktitle = {Workshop {Brainlesion}: {Glioma}, {Multiple} {Sclerosis}, {Stroke} and {Traumatic} {Brain} {Injuries}},
	author = {Wang, Guotai and Li, Wenqi and Ourselin, Sébastien and Vercauteren, Tom},
	year = {2018},
	keywords = {Convolutional neural network, Segmentation, Brain tumor},
	pages = {178--190},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/4MUWSNL2/Wang et al. - 2018 - Automatic Brain Tumor Segmentation Using Cascaded .pdf:application/pdf},
}

@inproceedings{bai_semi-supervised_2017,
	title = {Semi-supervised {Learning} for {Network}-{Based} {Cardiac} {MR} {Image} {Segmentation}},
	booktitle = {Medical {Image} {Computing} and {Computer}-{Assisted} {Intervention}},
	author = {Bai, Wenjia and Oktay, Ozan and Sinclair, Matthew and Suzuki, Hideaki and Rajchl, Martin and Tarroni, Giacomo and Glocker, Ben and King, Andrew and Matthews, Paul and Rueckert, Daniel},
	year = {2017},
	pages = {253--260},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/GHY2UTDE/Bai et al. - 2017 - Semi-supervised Learning for Network-Based Cardiac.pdf:application/pdf},
}

@article{fang_multi-organ_2020,
	title = {Multi-{Organ} {Segmentation} {Over} {Partially} {Labeled} {Datasets} {With} {Multi}-{Scale} {Feature} {Abstraction}},
	volume = {39},
	number = {11},
	journal = {IEEE Transactions on Medical Imaging},
	author = {Fang, Xi and Yan, Pingkun},
	year = {2020},
	keywords = {Image segmentation, deep learning, Annotations, Medical image segmentation, Biomedical imaging, convolutional neural networks, Feature extraction, Fuses, multi-organ segmentation, multi-scale feature, multiple datasets, Semantics, Training},
	pages = {3619--3629},
	file = {Accepted Version:/Users/benjamin/Zotero/storage/2VYANDZ5/Fang and Yan - 2020 - Multi-Organ Segmentation Over Partially Labeled Da.pdf:application/pdf;IEEE Xplore Abstract Record:/Users/benjamin/Zotero/storage/97VX6CM2/9112221.html:text/html},
}

@article{xu_federated_2023,
	title = {Federated {Multi}-{Organ} {Segmentation} {With} {Inconsistent} {Labels}},
	volume = {42},
	number = {10},
	journal = {IEEE Transactions on Medical Imaging},
	author = {Xu, Xuanang and Deng, Hannah and Gateno, Jamie and Yan, Pingkun},
	year = {2023},
	keywords = {Image segmentation, deep learning, Task analysis, Feature extraction, Training, Data models, Federated learning, Image analysis, inconsistent labels, medical image segmentation},
	pages = {2948--2960},
	file = {Accepted Version:/Users/benjamin/Zotero/storage/8EHC3PCW/Xu et al. - 2023 - Federated Multi-Organ Segmentation With Inconsiste.pdf:application/pdf;IEEE Xplore Abstract Record:/Users/benjamin/Zotero/storage/AZXR48ZI/10107904.html:text/html},
}

@misc{chen_med3d_2019,
	title = {{Med3D}: {Transfer} {Learning} for {3D} {Medical} {Image} {Analysis}},
	author = {Chen, Sihong and Ma, Kai and Zheng, Yefeng},
	year = {2019},
	note = {arXiv:1904.00625},
	keywords = {Computer Science - Computer Vision and Pattern Recognition},
	file = {arXiv Fulltext PDF:/Users/benjamin/Zotero/storage/SXMHAB7Z/Chen et al. - 2019 - Med3D Transfer Learning for 3D Medical Image Anal.pdf:application/pdf;arXiv.org Snapshot:/Users/benjamin/Zotero/storage/YB3HB2DX/1904.html:text/html},
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@article{shi_marginal_2021,
	title = {Marginal loss and exclusion loss for partially supervised multi-organ segmentation},
	volume = {70},
	journal = {Medical Image Analysis},
	author = {Shi, Gonglei and Xiao, Li and Chen, Yang and Zhou, Kevin},
	year = {2021},
	keywords = {Multi-organ segmentation, Exclusion loss, Marginal loss, Partially labeled dataset},
	file = {ScienceDirect Snapshot:/Users/benjamin/Zotero/storage/Q6JZAL89/S1361841521000256.html:text/html;Submitted Version:/Users/benjamin/Zotero/storage/EKWU8VJ5/Shi et al. - 2021 - Marginal loss and exclusion loss for partially sup.pdf:application/pdf},
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@article{isensee_nnu-net_2021,
	title = {{nnU}-{Net}: a self-configuring method for deep learning-based biomedical image segmentation},
	volume = {18},
	number = {2},
	journal = {Nature Methods},
	author = {Isensee, Fabian and Jaeger, Paul and Kohl, Simon and Petersen, Jens and Maier-Hein, Klaus},
	year = {2021},
	keywords = {Image processing, Translational research},
	pages = {203--211},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/YL4KERJG/Isensee et al. - 2021 - nnU-Net a self-configuring method for deep learni.pdf:application/pdf},
}

@inproceedings{jia_dynamic_2016,
	title = {Dynamic {Filter} {Networks}},
	volume = {29},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
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	year = {2016},
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@inproceedings{yang_condconv_2019,
	title = {{CondConv}: {Conditionally} {Parameterized} {Convolutions} for {Efficient} {Inference}},
	volume = {32},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
	author = {Yang, Brandon and Bender, Gabriel and Le, Quoc V and Ngiam, Jiquan},
	year = {2019},
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}

@inproceedings{chen_dynamic_2020,
	title = {Dynamic {Convolution}: {Attention} {Over} {Convolution} {Kernels}},
	booktitle = {Conference on {Computer} {Vision} and {Pattern} {Recognition}},
	author = {Chen, Yinpeng and Dai, Xiyang and Liu, Mengchen and Chen, Dongdong and Yuan, Lu and Liu, Zicheng},
	year = {2020},
	pages = {1030--1039},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/N6Q5FXBW/Chen et al. - 2020 - Dynamic Convolution Attention Over Convolution Ke.pdf:application/pdf},
}

@inproceedings{tian_conditional_2020,
	title = {Conditional {Convolutions} for {Instance} {Segmentation}},
	booktitle = {European {Conference} on {Computer} {Vision}},
	author = {Tian, Zhi and Shen, Chunhua and Chen, Hao},
	year = {2020},
	keywords = {Conditional convolutions, Instance segmentation},
	pages = {282--298},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/R7YPW9MC/Tian et al. - 2020 - Conditional Convolutions for Instance Segmentation.pdf:application/pdf},
}

@inproceedings{ha_hypernetworks_2017,
	title = {{HyperNetworks}},
	booktitle = {International {Conference} on {Learning} {Representations}},
	author = {Ha, David and Dai, Andrew and Le, Quoc V.},
	year = {2017},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/9XXA2HX8/Ha et al. - 2016 - HyperNetworks.pdf:application/pdf},
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@inproceedings{nirkin_hyperseg_2021,
	title = {{HyperSeg}: {Patch}-{Wise} {Hypernetwork} for {Real}-{Time} {Semantic} {Segmentation}},
	booktitle = {Conference on {Computer} {Vision} and {Pattern} {Recognition}},
	author = {Nirkin, Yuval and Wolf, Lior and Hassner, Tal},
	year = {2021},
	pages = {4061--4070},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/NXV2TMEI/Nirkin et al. - 2021 - HyperSeg Patch-Wise Hypernetwork for Real-Time Se.pdf:application/pdf},
}

@inproceedings{ma_hyper-convolution_2022,
	title = {Hyper-{Convolution} {Networks} for {Biomedical} {Image} {Segmentation}},
	booktitle = {Conference on {Applications} of {Computer} {Vision}},
	author = {Ma, Tianyu and Dalca, Adrian and Sabuncu, Mert},
	year = {2022},
	pages = {933--942},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/CD3XX62T/Ma et al. - 2022 - Hyper-Convolution Networks for Biomedical Image Se.pdf:application/pdf},
}

@misc{ortiz_magnitude_2023,
	title = {Magnitude {Invariant} {Parametrizations} {Improve} {Hypernetwork} {Learning}},
	author = {Ortiz, Jose Javier Gonzalez and Guttag, John and Dalca, Adrian},
	year = {2023},
	note = {arXiv:2304.07645},
	keywords = {Computer Science - Machine Learning, Computer Science - Artificial Intelligence},
	annote = {Comment: Source code at https://github.com/JJGO/hyperlight},
	file = {arXiv Fulltext PDF:/Users/benjamin/Zotero/storage/QP2XVX2X/Ortiz et al. - 2023 - Magnitude Invariant Parametrizations Improve Hyper.pdf:application/pdf;arXiv.org Snapshot:/Users/benjamin/Zotero/storage/FEJWHMIH/2304.html:text/html},
}

@article{perez_film_2018,
	title = {{FiLM}: {Visual} {Reasoning} with a {General} {Conditioning} {Layer}},
	volume = {32},
	number = {1},
	journal = {AAAI Conference on Artificial Intelligence},
	author = {Perez, Ethan and Strub, Florian and Vries, Harm de and Dumoulin, Vincent and Courville, Aaron},
	year = {2018},
	keywords = {Language and Vision},
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@inproceedings{lemay_benefits_2021,
	title = {Benefits of {Linear} {Conditioning} for {Segmentation} using {Metadata}},
	booktitle = {Medical {Imaging} with {Deep} {Learning}},
	author = {Lemay, Andreanne and Gros, Charley and Vincent, Olivier and Liu, Yaou and Cohen, Joseph Paul and Cohen-Adad, Julien},
	year = {2021},
	pages = {416--430},
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@inproceedings{lin_scribblesup_2016,
	title = {{ScribbleSup}: {Scribble}-{Supervised} {Convolutional} {Networks} for {Semantic} {Segmentation}},
	booktitle = {Conference on {Computer} {Vision} and {Pattern} {Recognition}},
	author = {Lin, Di and Dai, Jifeng and Jia, Jiaya and He, Kaiming and Sun, Jian},
	year = {2016},
	keywords = {Image segmentation, Labeling, Semantics, Training, Cows, Graphical models, Histograms},
	pages = {3159--3167},
	file = {IEEE Xplore Abstract Record:/Users/benjamin/Zotero/storage/KZA3M7FM/7780713.html:text/html;Submitted Version:/Users/benjamin/Zotero/storage/WZ6LAJ9F/Lin et al. - 2016 - ScribbleSup Scribble-Supervised Convolutional Net.pdf:application/pdf},
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@inproceedings{bearman_whats_2016,
	title = {What’s the {Point}: {Semantic} {Segmentation} with {Point} {Supervision}},
	booktitle = {European {Conference} on {Computer} {Vision}},
	author = {Bearman, Amy and Russakovsky, Olga and Ferrari, Vittorio and Fei-Fei, Li},
	year = {2016},
	keywords = {Data annotation, Semantic segmentation, Weak supervision},
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@inproceedings{papandreou_weakly-_2015,
	title = {Weakly- and {Semi}-{Supervised} {Learning} of a {Deep} {Convolutional} {Network} for {Semantic} {Image} {Segmentation}},
	booktitle = {International {Conference} on {Computer} {Vision}},
	author = {Papandreou, George and Chen, Liang and Murphy, Kevin and Yuille, Alan},
	year = {2015},
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@inproceedings{chartsias_multimodal_2020,
	title = {Multimodal {Cardiac} {Segmentation} {Using} {Disentangled} {Representation} {Learning}},
	booktitle = {Statistical {Atlases} and {Computational} {Models} of the {Heart}.},
	author = {Chartsias, Agisilaos and Papanastasiou, Giorgos and Wang, Chengjia and Stirrat, Colin and Semple, Scott and Newby, David and Dharmakumar, Rohan and Tsaftaris, Sotirios},
	year = {2020},
	keywords = {Cardiac MR, Disentanglement, Multimodal segmentation, Representation learning},
	pages = {128--137},
	file = {Full Text PDF:/Users/benjamin/Zotero/storage/244P79AG/Chartsias et al. - 2020 - Multimodal Cardiac Segmentation Using Disentangled.pdf:application/pdf},
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@inproceedings{dey_generative_2021,
	title = {Generative {Adversarial} {Registration} for {Improved} {Conditional} {Deformable} {Templates}},
	booktitle = {International {Conference} on {Computer} {Vision}},
	author = {Dey, Neel and Ren, Mengwei and Dalca, Adrian and Gerig, Guido},
	month = oct,
	year = {2021},
	keywords = {Neuroimaging, Magnetic resonance imaging, Medical, Training, and cell microscopy, biological, Estimation, Pediatrics, Sociology, Stochastic processes},
	pages = {3909--3921},
	file = {IEEE Xplore Abstract Record:/Users/benjamin/Zotero/storage/SKP5QYID/9711216.html:text/html;IEEE Xplore Full Text PDF:/Users/benjamin/Zotero/storage/YJ5DWXKD/Dey et al. - 2021 - Generative Adversarial Registration for Improved C.pdf:application/pdf},
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@inproceedings{zhu_multi-scale_2019,
	title = {Multi-scale {Coarse}-to-{Fine} {Segmentation} for {Screening} {Pancreatic} {Ductal} {Adenocarcinoma}},
	booktitle = {Medical {Image} {Computing} and {Computer} {Assisted} {Intervention}},
	author = {Zhu, Zhuotun and Xia, Yingda and Xie, Lingxi and Fishman, Elliot and Yuille, Alan},
	year = {2019},
	keywords = {CT scan, Pancreas segmentation, PDAC},
	pages = {3--12},
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	year = {2019},
	keywords = {Image segmentation, Computed tomography, Task analysis, Feature extraction, Training, crossbar-net, CT images, Deep convolutional neural network, image segmentation, Kidney, kidney tumors, Tumors},
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@inproceedings{zhang_light-weight_2019,
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	booktitle = {International {Joint} {Conference} on {Artificial} {Intelligence}},
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@inproceedings{dmitriev_learning_2019,
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@inproceedings{kalkhof_med-nca_2023,
	title = {Med-{NCA}: {Robust} and {Lightweight} {Segmentation} with {Neural} {Cellular} {Automata}},
	booktitle = {Information {Processing} in {Medical} {Imaging}},
	author = {Kalkhof, John and González, Camila and Mukhopadhyay, Anirban},
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@misc{billot_se3-equivariant_2023,
	title = {{SE}(3)-{Equivariant} and {Noise}-{Invariant} {3D} {Motion} {Tracking} in {Medical} {Images}},
	author = {Billot, Benjamin and Moyer, Daniel and Dey, Neel and Hoffmann, Malte and Turk, Esra Abaci and Gagoski, Borjan and Grant, Ellen and Golland, Polina},
	year = {2023},
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	keywords = {Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing},
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@article{hoffmann_synthmorph_2022,
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	author = {Hoffmann, Malte and Billot, Benjamin and Greve, Douglas and Iglesias, Juan Eugenio and Fischl, Bruce and Dalca, Adrian},
	year = {2022},
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@inproceedings{milletari_v-net_2016,
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@inproceedings{huang_arbitrary_2017,
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