8 papers
Segmenting Bi-Atrial Structures Using ResNext Based Framework
Malitha Gunawardhana, Mark L Trew, Gregory B Sands +1
Atrial Fibrillation (AF), the most common sustained cardiac arrhythmia worldwide, increasingly requires accurate bi-atrial structural assessment to guide ablation strategies, parti…
CrossVideoMAE: Self-Supervised Image-Video Representation Learning with Masked Autoencoders
Shihab Aaqil Ahamed, Malitha Gunawardhana, Liel David +3
Current video-based Masked Autoencoders (MAEs) primarily focus on learning effective spatiotemporal representations from a visual perspective, which may lead the model to prioritiz…
How good nnU-Net for Segmenting Cardiac MRI: A Comprehensive Evaluation
Malitha Gunawardhana, Fangqiang Xu, Jichao Zhao
Cardiac segmentation is a critical task in medical imaging, essential for detailed analysis of heart structures, which is crucial for diagnosing and treating various cardiovascular…
Integrating Deep Learning in Cardiology: A Comprehensive Review of Atrial Fibrillation, Left Atrial Scar Segmentation, and the Frontiers of State-of-the-Art Techniques
Malitha Gunawardhana, Anuradha Kulathilaka, Jichao Zhao
Atrial fibrillation (AFib) is the prominent cardiac arrhythmia in the world. It affects mostly the elderly population, with potential consequences such as stroke and heart failure…
How Effective are Self-Supervised Models for Contact Identification in Videos
Malitha Gunawardhana, Limalka Sadith, Liel David +2
The exploration of video content via Self-Supervised Learning (SSL) models has unveiled a dynamic field of study, emphasizing both the complex challenges and unique opportunities i…
Dynamic Position Transformation and Boundary Refinement Network for Left Atrial Segmentation
Fangqiang Xu, Wenxuan Tu, Fan Feng +4
Left atrial (LA) segmentation is a crucial technique for irregular heartbeat (i.e., atrial fibrillation) diagnosis. Most current methods for LA segmentation strictly assume that th…