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)

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)

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)

Differentially Private Graph Classification with GNNs. - Tamara T. Mueller; Johannes C. Paetzold; Chinmay Prabhakar; Dmitrii Usynin; Daniel Rueckert; Georgios Kaissis (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)

Self-pruning Graph Neural Network for Predicting Inflammatory Disease Activity in Multiple Sclerosis from Brain MR Images. - Chinmay Prabhakar; Hongwei Bran Li; Johannes C. Paetzold; Timo Loehr; Chen Niu; Mark Mühlau; Daniel Rueckert; Benedikt Wiestler; Bjoern H. Menze (MICCAI (8), 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)

Differentially Private Graph Neural Networks for Whole-Graph Classification. - Tamara T. Mueller; Johannes C. Paetzold; Chinmay Prabhakar; Dmitrii Usynin; Daniel Rueckert; Georgios Kaissis (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

GenerateCT: Text-Conditional Generation of 3D Chest CT Volumes. - Ibrahim Ethem Hamamci; Sezgin Er; Anjany Sekuboyina; Enis Simsar; Alperen Tezcan; Ayse Gulnihan Simsek; Sevval Nil Esirgun; Furkan Almas; Irem Dogan; Muhammed Furkan Dasdelen; Chinmay Prabhakar; Hadrien Reynaud; et al. (ECCV (79), 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)

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)

Link Prediction for Flow-Driven Spatial Networks. - Bastian Wittmann; Johannes C. Paetzold; Chinmay Prabhakar; Daniel Rueckert; Bjoern H. Menze (WACV, 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)

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