3 papers
eess.IV2025
U-R-VEDA: Integrating UNET, Residual Links, Edge and Dual Attention, and Vision Transformer for Accurate Semantic Segmentation of CMRs
Racheal Mukisa, Arvind K. Bansal
Artificial intelligence, including deep learning models, will play a transformative role in automated medical image analysis for the diagnosis of cardiac disorders and their manage…
eess.IV2025
DADU: Dual Attention-based Deep Supervised UNet for Automated Semantic Segmentation of Cardiac Images
Racheal Mukisa, Arvind K. Bansal
We propose an enhanced deep learning-based model for image segmentation of the left and right ventricles and myocardium scar tissue from cardiac magnetic resonance (CMR) images. Th…
eess.IV2025
Cardiac MRI Semantic Segmentation for Ventricles and Myocardium using Deep Learning
Racheal Mukisa, Arvind K. Bansal
Automated noninvasive cardiac diagnosis plays a critical role in the early detection of cardiac disorders and cost-effective clinical management. Automated diagnosis involves the a…