12 citations · 31 across the 10 of their papers we have counts for
10 papers
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…
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…
Vector Representations of Vessel Trees
James Batten, Michiel Schaap, Matthew Sinclair +2
We introduce a novel framework for learning vector representations of tree-structured geometric data focusing on 3D vascular networks. Our approach employs two sequentially trained…
A Diffusion Model for Simulation Ready Coronary Anatomy with Morpho-skeletal Control
Karim Kadry, Shreya Gupta, Jonas Sogbadji +6
Virtual interventions enable the physics-based simulation of device deployment within coronary arteries. This framework allows for counterfactual reasoning by deploying the same de…
Image To Tree with Recursive Prompting
James Batten, Matthew Sinclair, Ben Glocker +1
Extracting complex structures from grid-based data is a common key step in automated medical image analysis. The conventional solution to recovering tree-structured geometries typi…
Morphology-based non-rigid registration of coronary computed tomography and intravascular images through virtual catheter path optimization
Karim Kadry, Abhishek Karmakar, Andreas Schuh +6
Coronary computed tomography angiography (CCTA) provides 3D information on obstructive coronary artery disease, but cannot fully visualize high-resolution features within the vesse…