Patients with congenital cardiac disease are a vulnerable population who require early and repeat CT imaging. However, decreasing ionizing radiation dose in pediatric CT increases image noise. We evaluated a self-supervised deep learning denoising model integrating sparse coding with a modified Vision Transformer (SC-mViT) compared with a non-local means (NLM) algorithm using quantitative and qualitative metrics. Read More

Meeting name: SPR 2026 Annual Meeting , 2026

Authors: Gupta Ananya, Erkanli Alaattin, Badea Cristian, Cao Joseph, Clark Darin, Solomon Justin, Bache Steve, Janos Sara, Fadell Michael, Gaca Ana, Carrico Caroline, Morrison Samantha

Keywords: Congenital Heart, Artificial Intelligence, CT