386 citations · 393 across the 12 of their papers we have counts for
6 papers · 1 filter
VesselTok: Tokenizing Vessel-like 3D Biomedical Graph Representations for Reconstruction and Generation
Chinmay Prabhakar, Bastian Wittmann, Tamaz Amiranashvili +6
Spatial graphs provide a lightweight and elegant representation of curvilinear anatomical structures such as blood vessels, lung airways, and neuronal networks. Accurately modeling…
Semantically Consistent Discrete Diffusion for 3D Biological Graph Modeling
Chinmay Prabhakar, Suprosanna Shit, Tamaz Amiranashvili +2
3D spatial graphs play a crucial role in biological and clinical research by modeling anatomical networks such as blood vessels,neurons, and airways. However, generating 3D biologi…
Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization
Michal Balcerak, Tamaz Amiranashvili, Andreas Wagner +7
Physical models in the form of partial differential equations serve as important priors for many under-constrained problems. One such application is tumor treatment planning, which…
3D Vessel Graph Generation Using Denoising Diffusion
Chinmay Prabhakar, Suprosanna Shit, Fabio Musio +5
Blood vessel networks, represented as 3D graphs, help predict disease biomarkers, simulate blood flow, and aid in synthetic image generation, relevant in both clinical and pre-clin…
Landmark-free Statistical Shape Modeling via Neural Flow Deformations
David Lüdke, Tamaz Amiranashvili, Felix Ambellan +3
Statistical shape modeling aims at capturing shape variations of an anatomical structure that occur within a given population. Shape models are employed in many tasks, such as shap…
VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images
Anjany Sekuboyina, Malek E. Husseini, Amirhossein Bayat +66
Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit cl…