4 papers
Latent-to-Latent Flow for Volumetric Stochastic Segmentation
Omar Todd, Sooha Kim, Raghav Mehta +5
Uncertainty arising from inter-observer variability in medical image segmentation plays an important role in developing treatment plans. Research in this area is inhibited by the l…
GRC-ProbNet: Uncertainty-aware Feature Extraction for Cardiovascular Disease Classification
Yash Shah, Omar Todd, Philipp Seeböck +3
The automatic detection and classification of cardiovascular disease (CVD) from computed tomography (CT) images plays an important role in clinical practice. Recently, a hybrid pip…
Flow Stochastic Segmentation Networks
Fabio De Sousa Ribeiro, Omar Todd, Charles Jones +3
We introduce the Flow Stochastic Segmentation Network (Flow-SSN), a generative segmentation model family featuring discrete-time autoregressive and modern continuous-time flow vari…
Cardiovascular disease classification using radiomics and geometric features from cardiac CT
Ajay Mittal, Raghav Mehta, Omar Todd +3
Automatic detection and classification of Cardiovascular disease (CVD) from Computed Tomography (CT) images play an important part in facilitating better-informed clinical decision…