
CNNs perform automated staging of cardiac iron overload from multiecho MR sequences
This new European Radiology study aimed to develop a deep-learning model for classifying myocardial iron overload (MIO) using magnitude T2* multi-echo MR images from 496 thalassemia major patients. Two 2D convolutional neural networks (CNN), MS-HippoNet (multi-slice) and SS-HippoNet (single-slice), were trained using 5-fold cross-validation. The model showed strong performance with a multi-class accuracy of 0.885 and 0.836 on test sets,