6 citations · 9 across the 8 of their papers we have counts for
6 papers · 1 filter
Multi-Resolution Histopathology Patch Graphs for Ovarian Cancer Subtyping
Jack Breen, Katie Allen, Kieran Zucker +2
Computer vision models are increasingly capable of classifying ovarian epithelial cancer subtypes, but they differ from pathologists by processing small tissue patches at a single…
A Comprehensive Evaluation of Histopathology Foundation Models for Ovarian Cancer Subtype Classification
Jack Breen, Katie Allen, Kieran Zucker +3
Large pretrained transformers are increasingly being developed as generalised foundation models which can underpin powerful task-specific artificial intelligence models. Histopatho…
Segmenting Cardiac Muscle Z-disks with Deep Neural Networks
Mihaela Croitor Ibrahim, Nishant Ravikumar, Alistair Curd +3
Z-disks are complex structures that delineate repeating sarcomeres in striated muscle. They play significant roles in cardiomyocytes such as providing mechanical stability for the…
Reducing Histopathology Slide Magnification Improves the Accuracy and Speed of Ovarian Cancer Subtyping
Jack Breen, Katie Allen, Kieran Zucker +2
Artificial intelligence has found increasing use for ovarian cancer morphological subtyping from histopathology slides, but the optimal magnification for computational interpretati…
Multi-view Hybrid Graph Convolutional Network for Volume-to-mesh Reconstruction in Cardiovascular MRI
Nicolás Gaggion, Benjamin A. Matheson, Yan Xia +6
Cardiovascular magnetic resonance imaging is emerging as a crucial tool to examine cardiac morphology and function. Essential to this endeavour are anatomical 3D surface and volume…
Predicting Ovarian Cancer Treatment Response in Histopathology using Hierarchical Vision Transformers and Multiple Instance Learning
Jack Breen, Katie Allen, Kieran Zucker +3
For many patients, current ovarian cancer treatments offer limited clinical benefit. For some therapies, it is not possible to predict patients' responses, potentially exposing the…