5 citations · 5 across the 4 of their papers we have counts for
4 papers
Fake It Till You Make It: Using Synthetic Data and Domain Knowledge for Improved Text-Based Learning for LGE Detection
Athira J Jacob, Puneet Sharma, Daniel Rueckert
Detection of hyperenhancement from cardiac LGE MRI images is a complex task requiring significant clinical expertise. Although deep learning-based models have shown promising resul…
Towards a vision foundation model for comprehensive assessment of Cardiac MRI
Athira J Jacob, Indraneel Borgohain, Teodora Chitiboi +3
Cardiac magnetic resonance imaging (CMR), considered the gold standard for noninvasive cardiac assessment, is a diverse and complex modality requiring a wide variety of image proce…
DCSM 2.0: Deep Conditional Shape Models for Data Efficient Segmentation
Athira J Jacob, Puneet Sharma, Daniel Rueckert
Segmentation is often the first step in many medical image analyses workflows. Deep learning approaches, while giving state-of-the-art accuracies, are data intensive and do not sca…
Deep Conditional Shape Models for 3D cardiac image segmentation
Athira J Jacob, Puneet Sharma, Daniel Ruckert
Delineation of anatomical structures is often the first step of many medical image analysis workflows. While convolutional neural networks achieve high performance, these do not in…