most citedGSMorph: Gradient Surgery for cine-MRI Cardiac Deformable Registration

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eess.IV20241 cited

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…

eess.IV2023

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…

eess.IV2023

Learned Local Attention Maps for Synthesising Vessel Segmentations

Yash Deo, Rodrigo Bonazzola, Haoran Dou +5

Magnetic resonance angiography (MRA) is an imaging modality for visualising blood vessels. It is useful for several diagnostic applications and for assessing the risk of adverse ev…

eess.IV2023

Shape-guided Conditional Latent Diffusion Models for Synthesising Brain Vasculature

Yash Deo, Haoran Dou, Nishant Ravikumar +2

The Circle of Willis (CoW) is the part of cerebral vasculature responsible for delivering blood to the brain. Understanding the diverse anatomical variations and configurations of…

eess.IV2023

Adaptive Semi-Supervised Segmentation of Brain Vessels with Ambiguous Labels

Fengming Lin, Yan Xia, Nishant Ravikumar +3

Accurate segmentation of brain vessels is crucial for cerebrovascular disease diagnosis and treatment. However, existing methods face challenges in capturing small vessels and hand…

eess.IV2023

A Conditional Flow Variational Autoencoder for Controllable Synthesis of Virtual Populations of Anatomy

Haoran Dou, Nishant Ravikumar, Alejandro F. Frangi

The generation of virtual populations (VPs) of anatomy is essential for conducting in silico trials of medical devices. Typically, the generated VP should capture sufficient variab…