Table of Contents

• Preface1-4 [doi]
• Self-Rule to Adapt: Learning Generalized Features from Sparsely-Labeled Data Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue PhenotypingChristian Abbet, Linda Studer, Andreas Fischer, Heather Dawson, Inti Zlobec, Behzad Bozorgtabar, Jean-Philippe Thiran. 5-21 [doi]
• Stroke Lesion Outcome Prediction Based on 4D CT Perfusion Data Using Temporal Convolutional NetworksKimberly Amador, Matthias Wilms, Anthony J. Winder, Jens Fiehler, Nils D. Forkert. 22-33 [doi]
• Attention via Scattering Transforms for Segmentation of Small Intravascular Ultrasound Data SetsLennart Bargsten, Katharina A. Riedl, Tobias Wissel, Fabian J. Brunner, Klaus Schaefers, Michael Grass, Stefan Blankenberg, Moritz Seiffert, Alexander Schlaefer. 34-47 [doi]
• An MRF-UNet Product of Experts for Image SegmentationMikael Brudfors, Yaël Balbastre, John Ashburner, Geraint Rees 0001, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso. 48-59 [doi]
• Improving Weakly Supervised Lesion Segmentation using Multi-Task LearningTianshu Chu, Xinmeng Li, Huy V. Vo, Ronald M. Summers, Elena Sizikova. 60-73 [doi]
• Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-raysJoseph Paul Cohen, Rupert Brooks, Sovann EN, Evan Zucker, Anuj Pareek, Matthew P. Lungren, Akshay Chaudhari. 74-104 [doi]
• Semantic similarity metrics for learned image registrationSteffen Czolbe, Oswin Krause, Aasa Feragen. 105-118 [doi]
• M-GCN: A Multimodal Graph Convolutional Network to Integrate Functional and Structural Connectomics Data to Predict Multidimensional Phenotypic CharacterizationsNiharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman. 119-130 [doi]
• Improving MRI-based Knee Disorder Diagnosis with Pyramidal Feature DetailsMatteo Dunnhofer, Niki Martinel, Christian Micheloni. 131-147 [doi]
• Intensity Correction and Standardization for Electron Microscopy DataOleh Dzyubachyk, Roman I Koning, Aat A. Mulder, M. Christina Avramut, Frank G. A. Faas, Abraham J. Koster. 148-157 [doi]
• A Surprisingly Effective Perimeter-based Loss for Medical Image SegmentationRosana El Jurdi, Caroline Petitjean, Paul Honeine, Veronika Cheplygina, Fahed Abdallah. 158-167 [doi]
• Tailoring automated data augmentation to H&E-stained histopathologyKhrystyna Faryna, Jeroen van der Laak, Geert Litjens 0001. 168-178 [doi]
• Nuc2Vec: Learning Representations of Nuclei in Histopathology Images with Contrastive LossChao Feng, Chad M. Vanderbilt, Thomas J. Fuchs. 179-189 [doi]
• CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray SegmentationSoham Uday Gadgil, Mark Endo, Emily Wen, Andrew Y. Ng, Pranav Rajpurkar. 190-204 [doi]
• Self-supervised Out-of-distribution Detection for Cardiac CMR SegmentationCamila González, Anirban Mukhopadhyay 0003. 205-218 [doi]
• Direct Inference of Cell Positions using Lens-Free Microscopy and Deep LearningPhilipp Grüning, Falk Nette, Noah Heldt, Ana Cristina Guerra de Souza, Erhardt Barth. 219-227 [doi]
• Membership Inference Attacks on Deep Regression Models for NeuroimagingUmang Gupta, Dimitris Stripelis, Pradeep K. Lam, Paul M. Thompson, José Luis Ambite, Greg Ver Steeg. 228-251 [doi]
• Discrete Pseudohealthy Synthesis: Aortic Root Shape Typification and Type Classification with Pathological PriorJannis Hagenah, Floris Ernst. 252-267 [doi]
• Weakly Supervised Volumetric Segmentation via Self-taught Shape Denoising ModelQian He 0001, Shuailin Li, Xuming He 0001. 268-285 [doi]
• The OOD Blind Spot of Unsupervised Anomaly DetectionMatthäus Heer, Janis Postels, Xiaoran Chen, Ender Konukoglu, Shadi Albarqouni. 286-300 [doi]
• CNN and Deep Sets for End-to-End Whole Slide Image Representation LearningSobhan Hemati, Shivam Kalra, Cameron Meaney, Morteza Babaie, Ali Ghodsi 0001, Hamid R. Tizhoosh. 301-311 [doi]
• Whole-Body Soft-Tissue Lesion Tracking and Segmentation in Longitudinal CT Imaging StudiesAlessa Hering, Felix Peisen, Teresa Amaral, Sergios Gatidis, Thomas Eigentler, Ahmed Othman, Jan Hendrik Moltz. 312-326 [doi]
• Feedback Graph Attention Convolutional Network for MR Images Enhancement by Exploring Self-Similarity FeaturesXiaobin Hu, Yanyang Yan, Wenqi Ren, Hongwei Li, Amirhossein Bayat, Yu Zhao, Bjoern H. Menze. 327-337 [doi]
• Partial transfusion: on the expressive influence of trainable batch norm parameters for transfer learningFahdi Kanavati, Masayuki Tsuneki. 338-353 [doi]
• Beyond pixel-wise supervision for segmentation: A few global shape descriptors might be surprisingly good!Hoel Kervadec, Houda Bahig, Laurent Létourneau-Guillon, Jose Dolz, Ismail Ben Ayed. 354-368 [doi]
• Feature-based image registration in structured light endoscopyAndreas M. Kist, Julian Zilker, Michael Döllinger, Marion Semmler. 369-383 [doi]
• Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-temporal LSTM based Encoder-Decoder NetworkAishik Konwer, Joseph Bae, Gagandeep Singh, Rishabh Gattu, Syed Ali, Jeremy Green, Tej Phatak, Amit Gupta, Chao Chen 0012, Joel H. Saltz, Prateek Prasanna. 384-398 [doi]
• Embedding-based Instance Segmentation in MicroscopyManan Lalit, Pavel Tomancak, Florian Jug. 399-415 [doi]
• Benefits of Linear Conditioning for Segmentation using MetadataAndréanne Lemay, Charley Gros, Olivier Vincent, Yaou Liu, Joseph Paul Cohen, Julien Cohen-Adad. 416-430 [doi]
• Improved model-based deep learning for quantitative susceptibility mappingJuan Liu. 431-450 [doi]
• Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer DiagnosisKangning Liu, Yiqiu Shen, Nan Wu, Jakub Piotr Chledowski, Carlos Fernandez-Granda, Krzysztof J. Geras. 451-472 [doi]
• Distill DSM: Computationally efficient method for segmentation of medical imaging volumesHarsh Maheshwari, Vidit Goel, Ramanathan Sethuraman, Debdoot Sheet. 473-483 [doi]
• An AI-based Framework for Diagnostic Quality Assessment of Ankle RadiographsDominik Mairhöfer, Manuel Laufer, Paul Martin Simon, Malte Sieren, Arpad Bischof, Thomas Käster, Erhardt Barth, Jörg Barkhausen, Thomas Martinetz. 484-496 [doi]
• Unifying Brain Age Prediction and Age-Conditioned Template Generation with a Deterministic AutoencoderPauline Mouches, Matthias Wilms, Deepthi Rajashekar, Sönke Langner, Nils Daniel Forkert. 497-506 [doi]
• Learning Interclass Relations for Intravenous Contrast Phase Classification in CTRaouf Muhamedrahimov, Amir Bar, Ayelet Akselrod-Ballin. 507-519 [doi]
• EPIC-Survival: End-to-end Part Inferred Clustering for Survival Analysis, with Prognostic Stratification BoostingHassan Muhammad, Chensu Xie, Carlie S. Sigel, Michael Doukas, Lindsay Alpert, Amber Lea Simpson, Thomas J. Fuchs. 520-531 [doi]
• "Train one, Classify one, Teach one" - Cross-surgery transfer learning for surgical step recognitionDaniel Neimark, Omri Bar, Maya Zohar, Gregory D. Hager, Dotan Asselmann. 532-544 [doi]
• GOAL: Gist-set Online Active Learning for Efficient Chest X-ray Image AnnotationChanh Nguyen, Minh-Thanh Huynh, Minh Quan Tran, Ngoc Hoang Nguyen, Mudit Jain, Van Doan Ngo, Tan Duc Vo, Trung Bui, Steven Quoc Hung Truong. 545-553 [doi]
• Balanced sampling for an object detection problem - application to fetal anatomies detectionAntoine Olivier, Caroline Raynaud. 554-566 [doi]
• Explainable Image Quality Analysis of Chest X-RaysCaner Özer, Ilkay Öksüz. 567-580 [doi]
• Localizing Neurosurgical Instruments Across Domains and in the WildMarkus Philipp, Anna Alperovich, Marielena Gutt-Will, Andrea Mathis, Stefan Saur, Andreas Raabe, Franziska Mathis-Ullrich. 581-595 [doi]
• Unsupervised Brain Anomaly Detection and Segmentation with TransformersWalter Hugo Lopez Pinaya, Petru-Daniel Tudosiu, Robert Gray, Geraint Rees 0001, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso. 596-617 [doi]
• Residual learning for 3D motion corrected quantitative MRI: Robust clinical T1, T2 and proton density mappingCarolin M. Pirkl, Matteo Cencini, Jan W. Kurzawski, Diana Waldmannstetter, Hongwei Li, Anjany Sekuboyina, Sebastian Endt, Luca Peretti, Graziella Donatelli, Rosa Pasquariello, Michela Tosetti, Mauro Costagli, Guido Buonincontri, Marion I. Menzel, Bjoern H. Menze. 618-632 [doi]
• Image Sequence Generation and Analysis via GRU and Attention for Trachomatous Trichiasis ClassificationJuan-Carlos Prieto, Hina Shah, Kasey Jones, Robert F. Chew, Hashiya M. Kana, Jerusha Weaver, Rebecca M. Flueckiger, Scott McPherson, Emily W. Gower. 633-644 [doi]
• Learning Diffeomorphic and Modality-invariant Registration using B-splinesHuaqi Qiu, Chen Qin, Andreas Schuh, Kerstin Hammernik, Daniel Rueckert. 645-664 [doi]
• Understanding and Visualizing Generalization in UNetsAbhejit Rajagopal, Vamshi Chowdary Madala, Thomas A. Hope, Peder E. Z. Larson. 665-681 [doi]
• Cluster-to-Conquer: A Framework for End-to-End Multi-Instance Learning for Whole Slide Image ClassificationYash Sharma, Aman Shrivastava, Lubaina Ehsan, Christopher A. Moskaluk, Sana Syed, Donald E. Brown. 682-698 [doi]
• Unseen Disease Detection for Deep Learning Interpretation of Chest X-raysSiyu Shi, Ishaan Malhi, Kevin Tran, Andrew Y. Ng, Pranav Rajpurkar. 699-712 [doi]
• Changing the Contrast of Magnetic Resonance Imaging Signals using Deep LearningAttila Tibor Simkó, Tommy Löfstedt, Anders Garpebring, Mikael Bylund, Tufve Nyholm, Joakim Jonsson. 713-727 [doi]
• MoCo Pretraining Improves Representation and Transferability of Chest X-ray ModelsHari Sowrirajan, Jingbo Yang, Andrew Y. Ng, Pranav Rajpurkar. 728-744 [doi]
• A Mean-Field Variational Inference Approach to Deep Image Prior for Inverse Problems in Medical ImagingMalte Tölle, Max-Heinrich Laves, Alexander Schlaefer. 745-760 [doi]
• Learning the Latent Heat Diffusion Process through Structural Brain Network from Longitudinal β-Amyloid DataMd Asadullah Turja, Guorong Wu 0001, Defu Yang, Martin Andreas Styner. 761-773 [doi]
• Guided Filter Regularization for Improved Disentanglement of Shape and Appearance in Diffeomorphic AutoencodersHristina Uzunova, Heinz Handels, Jan Ehrhardt. 774-786 [doi]
• HAD-Net: A Hierarchical Adversarial Knowledge Distillation Network for Improved Enhanced Tumour Segmentation Without Post-Contrast ImagesSaverio Vadacchino, Raghav Mehta, Nazanin Mohammadi Sepahvand, Brennan Nichyporuk, James J. Clark, Tal Arbel. 787-801 [doi]
• Untangling the Small Intestine in 3D cine-MRI using Deep Stochastic TrackingLouis D. van Harten, Catharina de Jonge, Jaap Stoker, Ivana Isgum. 802-812 [doi]
• Automated triaging of head MRI examinations using convolutional neural networksDavid A. Wood 0004, Sina Kafiabadi, Aisha Al Busaidi, Emily Guilhem, Antanas Montvila, Siddharth Agarwal, Jeremy Lynch, Matthew Townend, Gareth Barker, Sebastian Ourselin, James H. Cole, Thomas C. Booth. 813-841 [doi]
• A regularization term for slide correlation reduction in whole slide image analysis with deep learningHongrun Zhang, Yanda Meng, Xuesheng Qian, Xiaoyun Yang, Sarah E. Coupland, Yalin Zheng. 842-854 [doi]
• SWNet: Surgical Workflow Recognition with Deep Convolutional NetworkBokai Zhang, Amer Ghanem, Alexander Simes, Henry Choi, Andrew Yoo, Andrew Min. 855-869 [doi]
• Hybrid optimization between iterative and network fine-tuning reconstructions for fast quantitative susceptibility mappingJinwei Zhang, Hang Zhang 0010, Pascal Spincemaille, Thanh D. Nguyen, Mert R. Sabuncu, Yi Wang 0028. 870-880 [doi]