Skip to content

Latest commit

 

History

History
360 lines (288 loc) · 28.3 KB

File metadata and controls

360 lines (288 loc) · 28.3 KB
layout title
default
Ahmad Sultan

News & Updates

Research Summary

  • Motion-robust Accelerated Cardiac Imaging: MRI data acquisition is inherently slow and susceptible to motion artifacts. Achieving clinically feasible imaging speeds requires a high degree of acceleration. Patients with arrhythmias or those unable to hold their breath, present further challenges. To address this, we have developed motion-robust self-supervised deep learning-based methods that preserve fine image details (often lost with conventional compressed sensing) at high accelerations, eliminating the need for breath-holds. Our approach produced higher-quality 2D cine, first-pass perfusion, and late gadolinium enhancement (LGE) images than traditional techniques, making cardiac MRI faster, more reliable and more accessible to patients who struggle with breath-holding or irregular heart rhythms.

Publications

Journal Articles

Conference Proceedings

Abstracts

Talks & Presentations

Oral Presentations

Poster Presentations