A Baseline for Predicting Glioblastoma Patient Survival Time with Classical Statistical Models and Primitive Features Ignoring Image Information. - Florian Kofler; Johannes C. Paetzold; Ivan Ezhov; Suprosanna Shit; Daniel Krahulec; Jan S. Kirschke; Claus Zimmer; Benedikt Wiestler; Bjoern H. Menze (BrainLes@MICCAI (1), 2019)

Neural Parameters Estimation for Brain Tumor Growth Modeling. - Ivan Ezhov; Jana Lipková; Suprosanna Shit; Florian Kofler; Nora Collomb; Benjamin Lemasson; Emmanuel Luc Barbier; Bjoern H. Menze (MICCAI (2), 2019)

Shape-Aware Complementary-Task Learning for Multi-organ Segmentation. - Fernando Navarro; Suprosanna Shit; Ivan Ezhov; Johannes C. Paetzold; Andrei Gafita; Jan C. Peeken; Stephanie E. Combs; Bjoern H. Menze (MLMI@MICCAI, 2019)

Implicit Neural Solver for Time-dependent Linear PDEs with Convergence Guarantee. - Suprosanna Shit; Abinav Ravi Venkatakrishnan; Ivan Ezhov; Jana Lipková; Marie Piraud; Bjoern H. Menze (CoRR, 2019)

A Distance-Based Loss for Smooth and Continuous Skin Layer Segmentation in Optoacoustic Images. - Stefan Gerl; Johannes C. Paetzold; Hailong He; Ivan Ezhov; Suprosanna Shit; Florian Kofler; Amirhossein Bayat; Giles Tetteh; Vasilis Ntziachristos; Bjoern H. Menze (MICCAI (6), 2020)

Aν-Net: Automatic Detection and Segmentation of Aneurysm. - Suprosanna Shit; Ivan Ezhov; Johannes C. Paetzold; Bjoern H. Menze (CADA@MICCAI, 2020)

Red-GAN: Attacking class imbalance via conditioned generation. Yet another medical imaging perspective. - Ahmad Bin Qasim; Ivan Ezhov; Suprosanna Shit; Oliver Schoppe; Johannes C. Paetzold; Anjany Sekuboyina; Florian Kofler; Jana Lipková; Hongwei Li 004; Bjoern H. Menze (MIDL, 2020)

VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images. - Anjany Sekuboyina; Malek El Husseini; Amirhossein Bayat; Maximilian Löffler; Hans Liebl; Hongwei Li 004; Giles Tetteh; Jan Kukacka; Christian Payer; Darko Stern; Martin Urschler; Maodong Chen; et al. (CoRR, 2020)

clDice - a Topology-Preserving Loss Function for Tubular Structure Segmentation. - Suprosanna Shit; Johannes C. Paetzold; Anjany Sekuboyina; Andrey Zhylka; Ivan Ezhov; Alexander Unger; Josien P. W. Pluim; Giles Tetteh; Bjoern H. Menze (CoRR, 2020)

Real-time Bayesian personalization via a learnable brain tumor growth model. - Ivan Ezhov; Tudor Mot; Suprosanna Shit; Jana Lipková; Johannes C. Paetzold; Florian Kofler; Fernando Navarro; Marie Metz; Benedikt Wiestler; Björn H. Menze (CoRR, 2020)

A comparison of automatic multi-tissue segmentation methods of the human fetal brain using the FeTA Dataset. - Kelly Payette; Priscille de Dumast; Hamza Kebiri; Ivan Ezhov; Johannes C. Paetzold; Suprosanna Shit; Asim Iqbal; Romesa Khan; Raimund Kottke; Patrice Grehten; Hui Ji; Levente Lanczi; et al. (CoRR, 2020)

Generalized Wasserstein Dice Loss, Test-Time Augmentation, and Transformers for the BraTS 2021 Challenge. - Lucas Fidon; Suprosanna Shit; Ivan Ezhov; Johannes C. Paetzold; Sébastien Ourselin; Tom Vercauteren (BrainLes@MICCAI (2), 2021)

FedCostWAvg: A New Averaging for Better Federated Learning. - Leon Mächler; Ivan Ezhov; Florian Kofler; Suprosanna Shit; Johannes C. Paetzold; Timo Loehr; Claus Zimmer; Benedikt Wiestler; Bjoern H. Menze (BrainLes@MICCAI (2), 2021)

clDice - A Novel Topology-Preserving Loss Function for Tubular Structure Segmentation. - Suprosanna Shit; Johannes C. Paetzold; Anjany Sekuboyina; Ivan Ezhov; Alexander Unger; Andrey Zhylka; Josien P. W. Pluim; Ulrich Bauer; Bjoern H. Menze (CVPR, 2021)

Velocity-To-Pressure (V2P) - Net: Inferring Relative Pressures from Time-Varying 3D Fluid Flow Velocities. - Suprosanna Shit; Dhritiman Das; Ivan Ezhov; Johannes C. Paetzold; Augusto Fava-Sanches; Nils Thuerey; Bjoern H. Menze (IPMI, 2021)

Imbalance-Aware Self-supervised Learning for 3D Radiomic Representations. - Hongwei Li 004; Fei-Fei Xue; Krishna Chaitanya; Shengda Luo; Ivan Ezhov; Benedikt Wiestler; Jianguo Zhang 001; Bjoern H. Menze (MICCAI (2), 2021)

Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience. - Johannes C. Paetzold; Julian McGinnis; Suprosanna Shit; Ivan Ezhov; Paul Büschl; Chinmay Prabhakar; Anjany Sekuboyina; Mihail I. Todorov; Georgios Kaissis; Ali Ertürk; Stephan Günnemann; Bjoern H. Menze (NeurIPS Datasets and Benchmarks, 2021)

Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations. - Hongwei Li 004; Fei-Fei Xue; Krishna Chaitanya; Shengda Liu; Ivan Ezhov; Benedikt Wiestler; Jianguo Zhang 001; Bjoern H. Menze (CoRR, 2021)

The MICCAI Hackathon on reproducibility, diversity, and selection of papers at the MICCAI conference. - Fabian Balsiger; Alain Jungo; Naren Akash R. J; Jianan Chen 001; Ivan Ezhov; Shengnan Liu; Jun Ma 016; Johannes C. Paetzold; Vishva Saravanan R; Anjany Sekuboyina; Suprosanna Shit; Yannick Suter; et al. (CoRR, 2021)

Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient. - Florian Kofler; Ivan Ezhov; Fabian Isensee; Fabian Balsiger; Christoph Berger; Maximilian Koerner; Johannes C. Paetzold; Hongwei Li 004; Suprosanna Shit; Richard McKinley; Spyridon Bakas; Claus Zimmer; et al. (CoRR, 2021)

Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience (VesselGraph). - Johannes C. Paetzold; Julian McGinnis; Suprosanna Shit; Ivan Ezhov; Paul Büschl; Chinmay Prabhakar; Mihail I. Todorov; Anjany Sekuboyina; Georgios Kaissis; Ali Ertürk; Stephan Günnemann; Bjoern H. Menze (CoRR, 2021)

Semi-Implicit Neural Solver for Time-dependent Partial Differential Equations. - Suprosanna Shit; Ivan Ezhov; Leon Mächler; Abinav R.; Jana Lipková; Johannes C. Paetzold; Florian Kofler; Marie Piraud; Bjoern H. Menze (CoRR, 2021)

FedCostWAvg: A new averaging for better Federated Learning. - Leon Mächler; Ivan Ezhov; Florian Kofler; Suprosanna Shit; Johannes C. Paetzold; Timo Loehr; Benedikt Wiestler; Bjoern H. Menze (CoRR, 2021)

VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images. - Anjany Sekuboyina; Malek El Husseini; Amirhossein Bayat; Maximilian Löffler; Hans Liebl; Hongwei Li 004; Giles Tetteh; Jan Kukacka; Christian Payer; Darko Stern; Martin Urschler; Maodong Chen; et al. (Medical Image Anal., 2021)

Deep Quality Estimation: Creating Surrogate Models for Human Quality Ratings. - Florian Kofler; Ivan Ezhov; Lucas Fidon; Izabela Horvath; Ezequiel de la Rosa; John LaMaster; Hongwei Li 004; Tom Finck; Suprosanna Shit; Johannes C. Paetzold; Spyridon Bakas; Marie Piraud; et al. (BrainLes@MICCAI, 2022)

FedPIDAvg: A PID Controller Inspired Aggregation Method for Federated Learning. - Leon Mächler; Ivan Ezhov; Suprosanna Shit; Johannes C. Paetzold (BrainLes@MICCAI (2), 2022)

Relationformer: A Unified Framework for Image-to-Graph Generation. - Suprosanna Shit; Rajat Koner; Bastian Wittmann; Johannes C. Paetzold; Ivan Ezhov; Hongwei Li 004; Jiazhen Pan; Sahand Sharifzadeh; Georgios Kaissis; Volker Tresp; Bjoern H. Menze (ECCV (37), 2022)

A Unified 3D Framework for Organs-at-Risk Localization and Segmentation for Radiation Therapy Planning. - Fernando Navarro; Guido Sasahara; Suprosanna Shit; Anjany Sekuboyina; Ivan Ezhov; Jan C. Peeken; Stephanie E. Combs; Bjoern H. Menze (EMBC, 2022)

Automated Analysis of Diabetic Retinopathy Using Vessel Segmentation Maps as Inductive Bias. - Linus Kreitner; Ivan Ezhov; Daniel Rueckert; Johannes C. Paetzold; Martin J. Menten (MIDOG/DRAC@MICCAI, 2022)

Landmark-Free Statistical Shape Modeling Via Neural Flow Deformations. - David Lüdke; Tamaz Amiranashvili; Felix Ambellan; Ivan Ezhov; Bjoern H. Menze; Stefan Zachow (MICCAI (2), 2022)

A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling. - Ivan Ezhov; Marcel Rosier; Lucas Zimmer; Florian Kofler; Suprosanna Shit; Johannes C. Paetzold; Kevin Scibilia; Felix Steinbauer; Leon Mächler; Katharina Franitza; Tamaz Amiranashvili; Martin J. Menten; et al. (ML4H@NeurIPS, 2022)

METGAN: Generative Tumour Inpainting and Modality Synthesis in Light Sheet Microscopy. - Izabela Horvath; Johannes C. Paetzold; Oliver Schoppe; Rami Al-Maskari; Ivan Ezhov; Suprosanna Shit; Hongwei Li 004; Ali Ertürk; Bjoern H. Menze (WACV, 2022)

A unified 3D framework for Organs at Risk Localization and Segmentation for Radiation Therapy Planning. - Fernando Navarro; Guido Sasahara; Suprosanna Shit; Ivan Ezhov; Jan C. Peeken; Stephanie E. Combs; Bjoern H. Menze (CoRR, 2022)

Casting the inverse problem as a database query. The case of personalized tumor growth modeling. - Ivan Ezhov; Marcel Rosier; Lucas Zimmer; Florian Kofler; Suprosanna Shit; Johannes C. Paetzold; Kevin Scibilia; Leon Mächler; Katharina Franitza; Tamaz Amiranashvili; Marie Metz; Sailesh Conjeti; et al. (CoRR, 2022)

ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset. - Moritz Roman Hernandez Petzsche; Ezequiel de la Rosa; Uta Hanning; Roland Wiest; Waldo Enrique Valenzuela Pinilla; Mauricio Reyes 001; Maria Inês Meyer; Sook-Lei Liew; Florian Kofler; Ivan Ezhov; David Robben; Alexandre Hutton; et al. (CoRR, 2022)

Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021. - Carole H. Sudre; Kimberlin M. H. van Wijnen; Florian Dubost; Hieab Adams; David Atkinson; Frederik Barkhof; Mahlet A. Birhanu; Esther E. Bron; Robin Camarasa; Nish Chaturvedi; Yuan Chen; Zihao Chen; et al. (CoRR, 2022)

SRflow: Deep learning based super-resolution of 4D-flow MRI data. - Suprosanna Shit; Judith Zimmermann; Ivan Ezhov; Johannes C. Paetzold; Augusto Fava-Sanches; Carolin M. Pirkl; Bjoern H. Menze (Frontiers Artif. Intell., 2022)

Geometry-Aware Neural Solver for Fast Bayesian Calibration of Brain Tumor Models. - Ivan Ezhov; Tudor Mot; Suprosanna Shit; Jana Lipková; Johannes C. Paetzold; Florian Kofler; Chantal Pellegrini; Marcel Kollovieh; Fernando Navarro; Hongwei Li 004; Marie Metz; Benedikt Wiestler; et al. (IEEE Trans. Medical Imaging, 2022)

Primitive Simultaneous Optimization of Similarity Metrics for Image Registration. - Diana Waldmannstetter; Benedikt Wiestler; Julian Schwarting; Ivan Ezhov; Marie Metz; Spyridon Bakas; Bhakti Baheti; Satrajit Chakrabarty; Daniel Rueckert; Jan S. Kirschke; Rolf A. Heckemann; Marie Piraud; et al. (BrainLes/SWITCH@MICCAI, 2023)

Why is the Winner the Best? - Matthias Eisenmann; Annika Reinke; Vivienn Weru; Minu Dietlinde Tizabi; Fabian Isensee; Tim J. Adler; Sharib Ali; Vincent Andrearczyk; Marc Aubreville; Ujjwal Baid; Spyridon Bakas; Niranjan Balu; et al. (CVPR, 2023)

A skeletonization algorithm for gradient-based optimization. - Martin J. Menten; Johannes C. Paetzold; Veronika A. Zimmer; Suprosanna Shit; Ivan Ezhov; Robbie Holland; Monika Probst; Julia A. Schnabel; Daniel Rueckert (ICCV, 2023)

blob loss: Instance Imbalance Aware Loss Functions for Semantic Segmentation. - Florian Kofler; Suprosanna Shit; Ivan Ezhov; Lucas Fidon; Izabela Horvath; Rami Al-Maskari; Hongwei Bran Li; Harsharan Bhatia; Timo Loehr; Marie Piraud; Ali Ertürk; Jan Kirschke; et al. (IPMI, 2023)

Approaching Peak Ground Truth. - Florian Kofler; Johannes Wahle; Ivan Ezhov; Sophia J. Wagner; Rami Al-Maskari; Emilia Gryska; Mihail I. Todorov; Christina Bukas; Felix Meissen; Tingying Peng; Ali Ertürk; Daniel Rueckert; et al. (ISBI, 2023)

Clustering Disease Trajectories in Contrastive Feature Space for Biomarker Proposal in Age-Related Macular Degeneration. - Robbie Holland; Oliver Leingang; Christopher Holmes; Philipp Anders; Rebecca Kaye; Sophie Riedl; Johannes C. Paetzold; Ivan Ezhov; Hrvoje Bogunovic; Ursula Schmidt-Erfurth; Hendrik P. N. Scholl; Sobha Sivaprasad; et al. (MICCAI (7), 2023)

Vesselformer: Towards Complete 3D Vessel Graph Generation from Images. - Chinmay Prabhakar; Suprosanna Shit; Johannes C. Paetzold; Ivan Ezhov; Rajat Koner; Hongwei Li 004; Florian Sebastian Kofler; Bjoern H. Menze (MIDL, 2023)

Primitive Simultaneous Optimization of Similarity Metrics for Image Registration. - Diana Waldmannstetter; Florian Kofler; Benedikt Wiestler; Julian Schwarting; Ivan Ezhov; Marie Metz; Daniel Rueckert; Jan S. Kirschke; Marie Piraud; Bjoern H. Menze (CoRR, 2023)

The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma. - Dominic LaBella; Maruf Adewole; Michelle Alonso-Basanta; Talissa Altes; Syed Muhammad Anwar; Ujjwal Baid; Timothy Bergquist; Radhika Bhalerao; Sully F. Chen; Verena Chung; Gian Marco Conte; Farouk Dako; et al. (CoRR, 2023)

The Brain Tumor Segmentation (BraTS) Challenge 2023: Local Synthesis of Healthy Brain Tissue via Inpainting. - Florian Kofler; Felix Meissen; Felix Steinbauer; Robert Graf; Eva Oswald; Ezequiel de la Rosa; Hongwei Bran Li; Ujjwal Baid; Florian A. Hölzl; Özgün Turgut; Izabela Horvath; Diana Waldmannstetter; et al. (CoRR, 2023)

The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn). - Hongwei Bran Li; Gian Marco Conte; Syed Muhammad Anwar; Florian Kofler; Koen Van Leemput; Marie Piraud; Ivan Ezhov; Felix Meissen; Maruf Adewole; Anastasia Janas; Anahita Fathi Kazerooni; Dominic LaBella; et al. (CoRR, 2023)

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs). - Anahita Fathi Kazerooni; Nastaran Khalili; Xinyang Liu; Debanjan Haldar; Zhifan Jiang; Syed Muhammad Anwar; Jake Albrecht; Maruf Adewole; Udunna Anazodo; Hannah Anderson; Sina Bagheri; Ujjwal Baid; et al. (CoRR, 2023)

Framing image registration as a landmark detection problem for better representation of clinical relevance. - Diana Waldmannstetter; Benedikt Wiestler; Julian Schwarting; Ivan Ezhov; Marie Metz; Spyridon Bakas; Bhakti Baheti; Satrajit Chakrabarty; Jan S. Kirschke; Rolf A. Heckemann; Marie Piraud; Florian Kofler; et al. (CoRR, 2023)

Panoptica - instance-wise evaluation of 3D semantic and instance segmentation maps. - Florian Kofler; Hendrik Kristian Möller; Josef A. Buchner; Ezequiel de la Rosa; Ivan Ezhov; Marcel Rosier; Isra Mekki; Suprosanna Shit; Moritz Negwer; Rami Al-Maskari; Ali Ertürk; Shankeeth Vinayahalingam; et al. (CoRR, 2023)

Individualizing Glioma Radiotherapy Planning by Optimization of a Data and Physics Informed Discrete Loss. - Michal Balcerak; Ivan Ezhov; Petr Karnakov; Sergey Litvinov; Petros Koumoutsakos; Jonas Weidner; Ray Zirui Zhang; John S. Lowengrub; Benedikt Wiestler; Bjoern H. Menze (CoRR, 2023)

Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA. - Kaiyuan Yang 003; Fabio Musio; Yihui Ma; Norman Juchler; Johannes C. Paetzold; Rami Al-Maskari; Luciano Höher; Hongwei Bran Li; Ibrahim Ethem Hamamci; Anjany Sekuboyina; Suprosanna Shit; Houjing Huang; et al. (CoRR, 2023)

The Liver Tumor Segmentation Benchmark (LiTS). - Patrick Bilic; Patrick Ferdinand Christ; Hongwei Li 004; Eugene Vorontsov; Avi Ben-Cohen; Georgios Kaissis; Adi Szeskin; Colin Jacobs; Gabriel Efrain Humpire Mamani; Gabriel Chartrand; Fabian Lohöfer; Julian Walter Holch; et al. (Medical Image Anal., 2023)

Learn-Morph-Infer: A new way of solving the inverse problem for brain tumor modeling. - Ivan Ezhov; Kevin Scibilia; Katharina Franitza; Felix Steinbauer; Suprosanna Shit; Lucas Zimmer; Jana Lipková; Florian Kofler; Johannes C. Paetzold; Luca Canalini; Diana Waldmannstetter; Martin J. Menten; et al. (Medical Image Anal., 2023)

Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization. - Michal Balcerak; Tamaz Amiranashvili; Andreas Wagner; Jonas Weidner; Petr Karnakov; Johannes C. Paetzold; Ivan Ezhov; Petros Koumoutsakos; Benedikt Wiestler; Bjoern H. Menze (NeurIPS, 2024)

MultiOrg: A Multi-rater Organoid-detection Dataset. - Christina Bukas; Harshavardhan Subramanian; Fenja See; Carina Steinchen; Ivan Ezhov; Gowtham Boosarpu; Sara Asgharpour; Gerald Burgstaller; Mareike Lehmann; Florian Kofler; Marie Piraud (NeurIPS, 2024)

A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge. - Ezequiel de la Rosa; Mauricio Reyes 001; Sook-Lei Liew; Alexandre Hutton; Roland Wiest; Johannes Kaesmacher; Uta Hanning; Arsany Hakim; Richard Zubal; Waldo Valenzuela; David Robben; Diana Maria Sima; et al. (CoRR, 2024)

The Brain Tumor Segmentation in Pediatrics (BraTS-PEDs) Challenge: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs). - Anahita Fathi Kazerooni; Nastaran Khalili; Deep Gandhi; Xinyang Liu; Zhifan Jiang; Syed Muhammed Anwar; Jake Albrecht; Maruf Adewole; Udunna Anazodo; Hannah Anderson; Sina Bagheri; Ujjwal Baid; et al. (CoRR, 2024)

Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge. - Dominic LaBella; Ujjwal Baid; Omaditya Khanna; Shan McBurney-Lin; Ryan McLean; Pierre Nedelec; Arif Rashid; Nourel Hoda Tahon; Talissa Altes; Radhika Bhalerao; Yaseen Dhemesh; Devon Godfrey; et al. (CoRR, 2024)

QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge. - Hongwei Bran Li; Fernando Navarro; Ivan Ezhov; Amirhossein Bayat; Dhritiman Das; Florian Kofler; Suprosanna Shit; Diana Waldmannstetter; Johannes C. Paetzold; Xiaobin Hu; Benedikt Wiestler; Lucas Zimmer; et al. (CoRR, 2024)

BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023. - Anahita Fathi Kazerooni; Nastaran Khalili; Xinyang Liu; Debanjan Haldar; Zhifan Jiang; Anna Zapaishchykova; Julija Pavaine; Lubdha M. Shah; Blaise V. Jones; Nakul Sheth; Sanjay P. Prabhu; Aaron S. McAllister; et al. (CoRR, 2024)

Don't You (Project Around Discs)? Neural Network Surrogate and Projected Gradient Descent for Calibrating an Intervertebral Disc Finite Element Model. - Matan Atad; Gabriel Gruber; Marx Ribeiro; Luis Fernando Nicolini; Robert Graf; Hendrik Kristian Möller; Kati Nispel; Ivan Ezhov; Daniel Rueckert; Jan S. Kirschke (CoRR, 2024)

FedPID: An Aggregation Method for Federated Learning. - Leon Mächler; Gustav Grimberg; Ivan Ezhov; Manuel Nickel; Suprosanna Shit; David Naccache; Johannes C. Paetzold (CoRR, 2024)

Spatial Brain Tumor Concentration Estimation for Individualized Radiotherapy Planning. - Jonas Weidner; Michal Balcerak; Ivan Ezhov; André Datchev; Laurin Lux; Lucas Zimmer; Daniel Rückert; Bjoern H. Menze; Benedikt Wiestler (CoRR, 2024)

Learnable personalization of brain tumor growth models (Lernbare Personalisierung von Hirntumor-Wachstumsmodellen) - Ivan Ezhov (2024)

Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021. - Carole H. Sudre; Kimberlin M. H. van Wijnen; Florian Dubost; Hieab Adams; David Atkinson; Frederik Barkhof; Mahlet A. Birhanu; Esther E. Bron; Robin Camarasa; Nish Chaturvedi; Yuan Chen; Zihao Chen; et al. (Medical Image Anal., 2024)

Machine Learning Analysis of Human Skin by Optoacoustic Mesoscopy for Automated Extraction of Psoriasis and Aging Biomarkers. - Hailong He; Johannes C. Paetzold; Nils Börner; Erik Riedel; Stefan Gerl; Simon Schneider; Chiara Fisher; Ivan Ezhov; Suprosanna Shit; Hongwei Li 004; Daniel Rückert; Juan Aguirre; et al. (IEEE Trans. Medical Imaging, 2024)

Efficient Deep Learning-based Forward Solvers for Brain Tumor Growth Models. - Zeineb Haouari; Jonas Weidner; Ivan Ezhov; Aswathi Varma; Daniel Rueckert; Bjoern H. Menze; Benedikt Wiestler (Bildverarbeitung für die Medizin, 2025)

Cross-Domain and Cross-Dimension Learning for Image-to-Graph Transformers. - Alexander H. Berger; Laurin Lux; Suprosanna Shit; Ivan Ezhov; Georgios Kaissis; Martin J. Menten; Daniel Rueckert; Johannes C. Paetzold (WACV, 2025)

Neural network surrogate and projected gradient descent for fast and reliable finite element model calibration: A case study on an intervertebral disc. - Matan Atad; Gabriel Gruber; Marx Ribeiro; Luis Fernando Nicolini; Robert Graf; Hendrik Kristian Möller; Kati Nispel; Ivan Ezhov; Daniel Rueckert; Jan S. Kirschke (Comput. Biol. Medicine, 2025)

Personalized predictions of Glioblastoma infiltration: Mathematical models, Physics-Informed Neural Networks and multimodal scans. - Ray Zirui Zhang; Ivan Ezhov; Michal Balcerak; Andy Zhu; Benedikt Wiestler; Bjoern H. Menze; John S. Lowengrub (Medical Image Anal., 2025)

A Learnable Prior Improves Inverse Tumor Growth Modeling. - Jonas Weidner; Ivan Ezhov; Michal Balcerak; Marie-Christin Metz; Sergey Litvinov; Sebastian Kaltenbach; Leonhard F. Feiner; Laurin Lux; Florian Kofler; Jana Lipková; Jonas Latz; Daniel Rueckert; et al. (IEEE Trans. Medical Imaging, 2025)

BraTS orchestrator : Democratizing and Disseminating state-of-the-art brain tumor image analysis. - Florian Kofler; Marcel Rosier; Mehdi Astaraki; Ujjwal Baid; Hendrik Kristian Möller; Josef A. Buchner; Felix Steinbauer; Eva Oswald; Ezequiel de la Rosa; Ivan Ezhov; Constantin von See; Jan Kirschke; et al. (CoRR, 2025)

BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis. - Florian Kofler; Marcel Rosier; Mehdi Astaraki; Hendrik Kristian Möller; Isra Mekki; Josef A. Buchner; Anton Schmick; Arianna Pfiffer; Eva Oswald; Lucas Zimmer; Ezequiel de la Rosa; Sarthak Pati; et al. (CoRR, 2025)

Enhancing efficiency in paediatric brain tumour segmentation using a pathologically diverse single-center clinical dataset. - Arianna Piffer; Josef A. Buchner; Gennari Antonio Giulio; Patrice Grehten; S. Sirin; E. Ross; Ivan Ezhov; Marcel Rosier; Jan Peeken; Marie Piraud; Bjoern H. Menze; A. Guerreiro Stücklin; et al. (CoRR, 2025)