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Journal Club

Taha Emre (2026). Time Equivariant Representation Learning for Longitudinal Medical Images of Degenerative Diseases. IEEE TMI; MICCAI 2024; arXiv.

Cite [1] IEEE TMI (3DTINC) [2] MICCAI 2024 [3] arXiv (STAMP)

Nico Schulthess (2026). Modeling DINO Embeddings for Fast and Efficient Unsupervised Anomaly Detection in Medical Imaging. MICCAI 2025.

Alessandro Crimi (2026). Graph Attention Networks for Detecting Epilepsy From EEG Signals Using Accessible Hardware in Low-Resource Settings. IEEE (Journal).

Kushal Vyas, Ashok Veeraraghavan, Guha Balakrishnan (2026). Implicit neural representations for signal representation and medical image segmentation. MICCAI 2025.

Akash Awasthi (2025). Agentic AI for radiology education.

Julia Wolleb, Florentin Bieder, Paul Friedrich, Hemant D. Tagare, Xenophon Papademetris (2025). VidFuncta: Towards Generalizable Neural Representations for Ultrasound Videos. MICCAI 2025.

Lasya Sreepada (2025). Deciphering Epigenetic Signatures of Aging and Neurodegeneration in Alzheimer's Disease with Machine Learning.

Fenqiang Zhao, Yuxing Tang, Le Lu, Ling Zhang (2025). A Curvature-Guided Coarse-to-Fine Framework for Enhanced Whole Brain Segmentation.

Special Session (2025). LISA Challenge: Low-field pediatric brain magnetic resonance Image Segmentation and quality Assurance Challenge.

Special Session (2025). MICCAI Lighthouse Challenge: Brain Tumor Segmentation Challenge.

Tabish Syed (2025). Cellular geometry of the heart.

Saurabh Sharma (2025). Confidence Matters: Enhancing Medical Image Classification Through Uncertainty-Driven Contrastive Self-Distillation.

Umang Pandey (2025). Learning Across Boundaries: Tackling Heterogeneity in Medical Federated Learning.

Pramit Saha (2025). Federated Medical Image Analysis: Shifting from data sharing to data access in Healthcare.

Arna Ghosh (2025). Bridging the conceptual gap between brains & AI: Representation learning.

Philippe Gottfrois (2025). PASSION for Dermatology: Bridging the Diversity Gap with Pigmented Skin Images from Sub-Saharan Africa.

Mengjin Dong (2025). Deep Learning for Detecting Progressive Changes in Alzheimer’s Disease. Imaging Neuroscience.

Special Session (2025). Ask us anything! Q&A session with MICCAI 2025 program chairs.

Mostafa Sharifzadeh, Sobhan Goudarzi, An Tang, Habib Benali, Hassan Rivaz (2024). Mitigating Aberration-Induced Noise: A Deep Learning-Based Aberration-to-Aberration Approach.

Xinrui Yuan (2024). Multi-task Joint Prediction of Infant Cortical Morphological and Cognitive Development.

Yiyang Xu, Hao Xu, Matthew Sinclair, Esther Puyol-Antón, Steven a Niederer, Amedeo Chiribiri, Steven E Williams, Michelle C Williams, Alistair a Young (2024). Improved 3D Whole Heart Geometry from Sparse CMR Slices.

Dewmini Hasara Wickremasinghe, Yiyang Xu, Esther Puyol-Antón, Paul Aljabar, Reza Razavi, Andrew P. King (2024). Improving the Scan-rescan Precision of AI-based CMR Biomarker Estimation.

Ahmed Nebli (2024). GRAM: Graph Regularizable Assessment Metric.

Paula Feldman, Miguel Fainstein, Viviana Siless, Claudio Delrieux, Emmanuel Iarussi (2024). VesselVAE: Recursive Variational Autoencoders for 3D Blood Vessel Synthesis.

Nahal Mirzaie (2024). Weakly-Supervised Drug Efficiency Estimation with Confidence Score: Application to COVID-19 Drug Discovery.

John Kalkhof, Anirban Mukhopadhyay (2024). M3D-NCA: Robust 3D Segmentation with Built-In Quality Control.

Gasper Podobnik (2024). HDilemma: Are Open-Source Hausdorff Distance Implementations Equivalent?.

DongAo Ma, Jiaxuan Pang, Michael B. Gotway, Jianming Liang (2024). Foundation Ark: Accruing and Reusing Knowledge for Superior and Robust Performance.

Alvaro Gonzalez-Jimenez, Simone Lionetti, Philippe Gottfrois, Fabian Gröger, Marc Pouly, Alexander Navarini (2024). Robust T-Loss for Medical Image Segmentation.

Pamela Guevara (2024). Superficial white matter bundle atlas based on hierarchical fiber clustering over probabilistic tractography data.

Raghav Mehta, Changjian Shui, Tal Arbel (2024). Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis.

Islem Rekik (2024). Special session: The journey of a research paper: from writing to review.

Heng Cai, Shumeng Li, Lei Qi, Qian Yu, Yinghuan Shi, Yang Gao (2024). Orthogonal annotation benefits barely-supervised medical image segmentation.

Scott M. Lundberg, Gabriel G. Erion, Su-in Lee (2024). Consistent Individualized Feature Attribution for Tree Ensembles.

Annika Reinke, Minu D. Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Carole H. Sudre, Laura Acion, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Matthew Blaschko, Florian Buettner, M. Jorge Cardoso, Veronika Cheplygina, Jianxu Chen, Evangelia Christodoulou, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram Van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Jens Kleesiek, Florian Kofler, Thijs Kooi, Annette Kopp-Schneider, Michal Kozubek, Anna Kreshuk, Tahsin Kurc, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern Menze, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Susanne M. Rafelski, Nasir Rajpoot, Mauricio Reyes, Michael A. Riegler, Nicola Rieke, Julio Saez-Rodriguez, Clara I. Sánchez, Shravya Shetty, Maarten Van Smeden, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben Van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul F. Jäger, Lena Maier-Hein (2024). Understanding metric-related pitfalls in image analysis validation. Nature Methods.

Qiang Zhang (2024). Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy and Artificial intelligence for contrast-free MRI: Scar assessment in myocardial infarction using deep learning–based virtual native enhancement.

Charles Delahunt, Andrea Lara, Ahmed Shahin, Tareen Dawood, Esther Puyol (2024). Opening session multi-linguistic: french, spanish, english, arabic.

Tiarna Lee, Esther Puyol-Antón, Bram Ruijsink, Keana Aitcheson, Miaojing Shi, Andrew P. King (2023). An investigation into the impact of deep learning model choice on sex and race bias in cardiac MR segmentation.

Prosper Oyibo (2023). Two-stage automated diagnosis framework for urogenital schistosomiasis in microscopy images from low-resource settings.

Tareen Dawood (2023). Uncertainty aware training to improve deep learning model calibration for classification of cardiac MR images.

Prerak Mody, Mortiz Fuchs (2023). Prediction Variability to Identify Reduced AI Performance in Cancer Diagnosis at MRI and CT.

Konpat Preechakul, Nattanat Chatthee, Suttisak Wizadwongsa, Supasorn Suwajanakorn (2023). Diffusion Autoencoders: Toward a Meaningful and Decodable Representation.

Charles B. Delahunt, Noni Gachuhi, Matthew P. Horning (2023). Metrics to guide development of machine learning algorithms for malaria diagnosis.

Le Zhang, Ryutaro Tanno, Mou-Cheng Xu, Chen Jin, Joseph Jacob, Olga Ciccarelli, Frederik Barkhof, Daniel C. Alexander (2023). Disentangling human error from the ground truth in segmentation of medical images.

Yuting He, Guanyu Yang, Rongjun Ge, Yang Chen, Jean-Louis Coatrieux, Boyu Wang, Shuo Li (2023). Geometric Visual Similarity Learning in 3D Medical Image Self-supervised Pre-training.

Paul Jacob, Éloi Zablocki, Hédi Ben-Younes, Mickaël Chen, Patrick Pérez, Matthieu Cord (2023). STEEX: Steering Counterfactual Explanations with semantics.

Enmao Diao, Jie Ding, Vahid Tarokh (2023). HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients.

Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin (2023). Attention Is All You Need.

Yi Zhang, Arushi Gupta, Nikunj Saunshi, Sanjeev Arora (2023). On Predicting Generalization using GANs.

Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, Dhruv Batra (2023). Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization.

Jonathon Shlens (2023). A Tutorial on Principal Component Analysis.

Steven Goodman (2023). A dirty dozen: 12 p-value misconceptions.

Satrajit Chatterjee (2023). Coherent Gradients: An Approach to Understanding Generalization in Gradient Descent-based Optimization. ICLR 2020.

Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton (2023). Imagenet classification with deep convolutional neural networks.

Khosro Bahrami, Feng Shi, Xiaopeng Zong, Hae Won Shin, Hongyu An, Dinggang Shen (2023). Hierarchical Reconstruction of 7T-like Images from 3T MRI Using Multi-level CCA and Group Sparsity. MICCAI 2015.