A two-stage deep learning framework segments ten GI organs from coronal MR enterography images, achieving mean DSC of 88.99% and outperforming baselines.
Metrics for evaluating 3D medical image segmentation: Analysis, selection, and tool
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A Two-Stage Deep Learning Framework for Segmentation of Ten Gastrointestinal Organs from Coronal MR Enterography
A two-stage deep learning framework segments ten GI organs from coronal MR enterography images, achieving mean DSC of 88.99% and outperforming baselines.