activity
20202026
most citedImproved 3D Whole Heart Geometry from Sparse CMR Slices

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Beyond Volume Overlap: Surface Matching for Topology-Aware Coronary Artery Segmentation

Rafael Velasquez, Esther Puyol-Antón, Pablo Arbeláez

Accurate coronary artery segmentation on coronary computed tomography angiography (CCTA) is essential for diagnosing coronary artery disease. Deep networks are conventionally train…

cs.CV2026

Positional Segmentor-Guided Counterfactual Fine-Tuning for Spatially Localized Image Synthesis

Tian Xia, Matthew Sinclair, Andreas Schuh +8

Counterfactual image generation enables controlled data augmentation, bias mitigation, and disease modeling. However, existing methods guided by external classifiers or regressors…

cs.CV2025

Segmentor-Guided Counterfactual Fine-Tuning for Locally Coherent and Targeted Image Synthesis

Tian Xia, Matthew Sinclair, Andreas Schuh +8

Counterfactual image generation is a powerful tool for augmenting training data, de-biasing datasets, and modeling disease. Current approaches rely on external classifiers or regre…

eess.IV2024★ 2 cited

Improved 3D Whole Heart Geometry from Sparse CMR Slices

Yiyang Xu, Hao Xu, Matthew Sinclair +6

Cardiac magnetic resonance (CMR) imaging and computed tomography (CT) are two common non-invasive imaging methods for assessing patients with cardiovascular disease. CMR typically…

cs.CV2020

Probabilistic 3D surface reconstruction from sparse MRI information

Katarína Tóthová, Sarah Parisot, Matthew Lee +4

Surface reconstruction from magnetic resonance (MR) imaging data is indispensable in medical image analysis and clinical research. A reliable and effective reconstruction tool shou…