5 citations · 5 across the 7 of their papers we have counts for
7 papers
CMRVision: A Foundation Model for Cardiac MR Image Analysis
Athira J. Jacob, Puneet Sharma, Daniel Rueckert
Cardiac magnetic resonance (CMR) imaging provides complementary information on cardiac anatomy, function, and tissue characterization across multiple sequences and views. In this w…
MR-JEPA: A General Purpose Video Foundation Model for Cardiac MRI
Athira J. Jacob, Puneet Sharma, Dorin Comaniciu +1
Cardiac magnetic resonance imaging (CMR) produces rich sequential data such as temporal cine videos and spatial LGE/mapping stacks, yet most deep learning approaches process indivi…
LGESynthNet: Controlled Scar Synthesis for Improved Scar Segmentation in Cardiac LGE-MRI Imaging
Athira J. Jacob, Puneet Sharma, Daniel Rueckert
Segmentation of enhancement in LGE cardiac MRI is critical for diagnosing various ischemic and non-ischemic cardiomyopathies. However, creating pixel-level annotations for these im…
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…