SNRAware: Improved Deep Learning MRI Denoising with Signal-to-Noise Ratio Unit Training and G-Factor Map Augmentation

作者：Hui Xue, Sarah Hooper, Iain Pierce, Rhodri Davies, John Stairs, Joseph Naegele, Adrienne Campbell‐Washburn, Charlotte Manisty, James Moon, Thomas A. Treibel, Michael S. Hansen, Peter Kellman · 发表于：Radiology Artificial Intelligence · 年份：2025 · DOI：10.1148/ryai.250227 · 被引用次数：2 · 研究领域：Advanced MRI Techniques and Applications、Cardiac Imaging and Diagnostics、Advanced Neuroimaging Techniques and Applications

SNRAware, a model-agnostic approach for training MRI denoising models that leverages information from the image reconstruction process, improved performance and enhanced generalization to unseen imaging applications.