A low cost data acquisition system from digital display instruments employing image processing technique. - Soumyadip Ghosh; Suprosanna Shit (ICACCI, 2014)

Phasesplit: A Variable Splitting Framework for Phase Retrieval. - Subhadip Mukherjee; Suprosanna Shit; Chandra Sekhar Seelamantula (ICASSP, 2018)

Training-Free, Single-Image Super-Resolution Using a Dynamic Convolutional Network. - Aritra Bhowmik; Suprosanna Shit; Chandra Sekhar Seelamantula (IEEE Signal Process. Lett., 2018)

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)

Cranial Implant Prediction Using Low-Resolution 3D Shape Completion and High-Resolution 2D Refinement. - Amirhossein Bayat; Suprosanna Shit; Adrian Kilian; Jürgen T. Liechtenstein; Jan S. Kirschke; Bjoern H. Menze (AutoImplant@MICCAI, 2020)

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)

Complex Grey Matter Structure Segmentation in Brains via Deep Learning: Example of the Claustrum. - Hongwei Li 004; Aurore Menegaux; Felix J. B. Bäuerlein; Suprosanna Shit; Benita Schmitz-Koep; Christian Sorg; Bjoern H. Menze; Dennis M. Hedderich (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)

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)

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)

Evaluating the Robustness of Self-Supervised Learning in Medical Imaging. - Fernando Navarro; Christopher Watanabe; Suprosanna Shit; Anjany Sekuboyina; Jan C. Peeken; Stephanie E. Combs; Bjoern H. Menze (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)

Partial supervision for the FeTA challenge 2021. - Lucas Fidon; Michael Aertsen; Suprosanna Shit; Philippe Demaerel; Sébastien Ourselin; Jan Deprest; Tom Vercauteren (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)

Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: The ADAM challenge. - Kimberley M. Timmins; Irene C. van der Schaaf; Edwin Bennink; Ynte M. Ruigrok; Xingle An; Michael Baumgartner 001; Pascal Bourdon; Riccardo de Feo; Tommaso Di Noto; Florian Dubost; Augusto Fava-Sanches; Xue Feng 001; et al. (NeuroImage, 2021)

AutoImplant 2020-First MICCAI Challenge on Automatic Cranial Implant Design. - Jianning Li 002; Pedro Pimentel; Angelika Szengel; Moritz Ehlke; Hans Lamecker; Stefan Zachow; Laura Jovani Estacio Cerquin; Christian Doenitz; Heiko Ramm; Haochen Shi; Xiaojun Chen 003; Franco Matzkin; et al. (IEEE Trans. Medical Imaging, 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)

Self-Supervised Pretext Tasks in Model Robustness & Generalizability: A Revisit from Medical Imaging Perspective. - Fernando Navarro; Christopher Watanabe; Suprosanna Shit; Anjany Sekuboyina; Jan C. Peeken; Stephanie E. Combs; Bjoern H. Menze (EMBC, 2022)

Structured Knowledge Graphs for Classifying Unseen Patterns in Radiographs. - Chinmay Prabhakar; Anjany Sekuboyina; Hongwei Bran Li; Johannes C. Paetzold; Suprosanna Shit; Tamaz Amiranashvili; Jens Kleesiek; Bjoern H. Menze (GeoMedIA, 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)

Focused Decoding Enables 3D Anatomical Detection by Transformers. - Bastian Wittmann; Fernando Navarro; Suprosanna Shit; Bjoern H. Menze (CoRR, 2022)

A Domain-specific Perceptual Metric via Contrastive Self-supervised Representation: Applications on Natural and Medical Images. - Hongwei Bran Li; Chinmay Prabhakar; Suprosanna Shit; Johannes C. Paetzold; Tamaz Amiranashvili; Jianguo Zhang 001; Daniel Rueckert; Juan Eugenio Iglesias; Benedikt Wiestler; Bjoern H. Menze (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)

Detection and analysis of cerebral aneurysms based on X-ray rotational angiography - the CADA 2020 challenge. - Matthias Ivantsits; Leonid Goubergrits; Jan-Martin Kuhnigk; Markus Hüllebrand; Jan Brüning; Tabea Kossen; Boris Pfahringer; Jens Schaller; Andreas Spuler; Titus Kühne; Yizhuan Jia; Xuesong Li 003; et al. (Medical Image Anal., 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)

InstanceFormer: An Online Video Instance Segmentation Framework. - Rajat Koner; Tanveer Hannan; Suprosanna Shit; Sahand Sharifzadeh; Matthias Schubert; Thomas Seidl 001; Volker Tresp (AAAI, 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)

Topologically Faithful Image Segmentation via Induced Matching of Persistence Barcodes. - Nico Stucki; Johannes C. Paetzold; Suprosanna Shit; Bjoern H. Menze; Ulrich Bauer (ICML, 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)

Pushing the Limits of an FCN and A CRF Towards Near-Ideal Vertebrae Labelling. - Anjany Sekuboyina; Jannik Irmai; Suprosanna Shit; Jan Kirschke; Bjoern Andres; Bjoern H. Menze (ISBI, 2023)

Single-subject Multi-contrast MRI Super-resolution via Implicit Neural Representations. - Julian McGinnis; Suprosanna Shit; Hongwei Bran Li; Vasiliki Sideri-Lampretsa; Robert Graf; Maik Dannecker; Jiazhen Pan; Nil Stolt Ansó; Mark Mühlau; Jan S. Kirschke; Daniel Rueckert; Benedikt Wiestler (MICCAI (8), 2023)

Global k-Space Interpolation for Dynamic MRI Reconstruction Using Masked Image Modeling. - Jiazhen Pan; Suprosanna Shit; Özgün Turgut; Wenqi Huang 003; Hongwei Bran Li; Nil Stolt Ansó; Thomas Küstner; Kerstin Hammernik; Daniel Rueckert (MICCAI (10), 2023)

ViT-AE++: Improving Vision Transformer Autoencoder for Self-supervised Medical Image Representations. - Chinmay Prabhakar; Hongwei Li 004; Jiancheng Yang; Suprosanna Shit; Benedikt Wiestler; Bjoern H. Menze (MIDL, 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)

Multi-contrast MRI Super-resolution via Implicit Neural Representations. - Julian McGinnis; Suprosanna Shit; Hongwei Bran Li; Vasiliki Sideri-Lampretsa; Robert Graf; Maik Dannecker; Jiazhen Pan; Nil Stolt Ansó; Mark Mühlau; Jan S. Kirschke; Daniel Rueckert; Benedikt Wiestler (CoRR, 2023)

GRAtt-VIS: Gated Residual Attention for Auto Rectifying Video Instance Segmentation. - Tanveer Hannan; Rajat Koner; Maximilian Bernhard; Suprosanna Shit; Bjoern H. Menze; Volker Tresp; Matthias Schubert; Thomas Seidl 001 (CoRR, 2023)

Unlocking the Diagnostic Potential of ECG through Knowledge Transfer from Cardiac MRI. - Özgün Turgut; Philip Müller; Paul Hager; Suprosanna Shit; Sophie Starck; Martin J. Menten; Eimo Martens; Daniel Rueckert (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)

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)

GRAtt-VIS: Gated Residual Attention for Video Instance Segmentation. - Tanveer Hannan; Rajat Koner; Maximilian Bernhard; Suprosanna Shit; Bjoern H. Menze; Volker Tresp; Matthias Schubert; Thomas Seidl 001 (ICPR (16), 2024)

Supervised Contrastive Learning for Image-to-Graph Transformers. - Anna Banaszak; Alexander H. Berger; Laurin Lux; Suprosanna Shit; Daniel Rueckert; Johannes C. Paetzold (GRAIL@MICCAI, 2024)

Topologically Faithful Multi-class Segmentation in Medical Images. - Alexander H. Berger; Laurin Lux; Nico Stucki; Vincent Bürgin; Suprosanna Shit; Anna Banaszak; Daniel Rueckert; Ulrich Bauer; Johannes C. Paetzold (MICCAI (8), 2024)

3D Vessel Graph Generation Using Denoising Diffusion. - Chinmay Prabhakar; Suprosanna Shit; Fabio Musio; Kaiyuan Yang 003; Tamaz Amiranashvili; Johannes C. Paetzold; Hongwei Bran Li; Bjoern H. Menze (MICCAI (11), 2024)

Whole Heart 3D+T Representation Learning Through Sparse 2D Cardiac MR Images. - Yundi Zhang; Chen Chen 042; Suprosanna Shit; Sophie Starck; Daniel Rueckert; Jiazhen Pan (MICCAI (1), 2024)

Modeling the acquisition shift between axial and sagittal MRI for diffusion superresolution to enable axial spine segmentation. - Robert Graf; Hendrik Kristian Möller; Julian McGinnis; Sebastian Rühling; Maren Weihrauch; Matan Atad; Suprosanna Shit; Bjoern H. Menze; Mark Mühlau; Johannes C. Paetzold; Daniel Rueckert; Jan Kirschke (MIDL, 2024)

VariViT: A Vision Transformer for Variable Image Sizes. - Aswathi Varma; Suprosanna Shit; Chinmay Prabhakar; Daniel Scholz 005; Hongwei Bran Li; Bjoern H. Menze; Daniel Rueckert; Benedikt Wiestler (MIDL, 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)

Enhancing Interpretability of Vertebrae Fracture Grading using Human-interpretable Prototypes. - Poulami Sinhamahapatra; Suprosanna Shit; Anjany Sekuboyina; Malek El Husseini; David Schinz; Nicolas Lenhart; Bjoern H. Menze; Jan Kirschke; Karsten Roscher; Stephan Günnemann (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)

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

vesselFM: A Foundation Model for Universal 3D Blood Vessel Segmentation. - Bastian Wittmann; Yannick Wattenberg; Tamaz Amiranashvili; Suprosanna Shit; Bjoern H. Menze (CVPR, 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)

Corrigendum to "Detection and analysis of cerebral aneurysms based on X-ray rotational angiography - the CADA 2020 challenge" [Medical Image Analysis, April 2022, Volume 77, 102333]. - Matthias Ivantsits; Leonid Goubergrits; Jan-Martin Kuhnigk; Markus Hüllebrand; Jan Brüning; Tabea Kossen; Boris Pfahringer; Jens Schaller; Andreas Spuler; Titus Kühne; Yizhuan Jia; Xuesong Li 003; et al. (Medical Image Anal., 2025)

Unlocking the diagnostic potential of electrocardiograms through information transfer from cardiac magnetic resonance imaging. - Özgün Turgut; Philip Müller; Paul Hager; Suprosanna Shit; Sophie Starck; Martin J. Menten; Eimo Martens; Daniel Rueckert (Medical Image Anal., 2025)

Towards cardiac MRI foundation models: Comprehensive visual-tabular representations for whole-heart assessment and beyond. - Yundi Zhang; Paul Hager; Che Liu; Suprosanna Shit; Chen Chen 042; Daniel Rueckert; Jiazhen Pan (Medical Image Anal., 2025)

Energy Matching: Unifying Flow Matching and Energy-Based Models for Generative Modeling. - Michal Balcerak; Tamaz Amiranashvili; Suprosanna Shit; Antonio Terpin; Sebastian Kaltenbach; Petros Koumoutsakos; Bjoern H. Menze (CoRR, 2025)

CRG Score: A Distribution-Aware Clinical Metric for Radiology Report Generation. - Ibrahim Ethem Hamamci; Sezgin Er; Suprosanna Shit; Hadrien Reynaud; Bernhard Kainz; Bjoern H. Menze (CoRR, 2025)

Parametric shape models for vessels learned from segmentations via differentiable voxelization. - Alina F. Dima; Suprosanna Shit; Huaqi Qiu; Robbie Holland; Tamara T. Mueller; Fabio Musio; Kaiyuan Yang 003; Bjoern H. Menze; Rickmer Braren; Marcus R. Makowski; Daniel Rueckert (CoRR, 2025)

Semantically Consistent Discrete Diffusion for 3D Biological Graph Modeling. - Chinmay Prabhakar; Suprosanna Shit; Tamaz Amiranashvili; Hongwei Bran Li; Bjoern H. Menze (CoRR, 2025)

Reconstruct or Generate: Exploring the Spectrum of Generative Modeling for Cardiac MRI. - Niklas Bubeck; Yundi Zhang; Suprosanna Shit; Daniel Rueckert; Jiazhen Pan (CoRR, 2025)

CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography. - Murong Xu; Tamaz Amiranashvili; Fernando Navarro; Maksym Fritsak; Ibrahim Ethem Hamamci; Suprosanna Shit; Bastian Wittmann; Sezgin Er; Sebastian M. Christ; Ezequiel de la Rosa; Julian Deseoe; Robert Graf; et al. (CoRR, 2025)