MRSegmentator is a novel deep learning model that accurately and robustly segments 40 anatomical structures in both MRI and CT images, addressing the limitations of existing organ-specific approaches and offering a valuable tool for automated multi-organ segmentation in medical imaging research.
The authors propose Densely Decoded Networks (DDN) with Adaptive Deep Supervision (ADS) to improve medical image segmentation by refining dense prediction and enhancing feature extraction.