A three-stage pipeline detects 16 landmarks, coarsely segments 12 labels, and refines them into 26 structures using landmark constraints to improve accuracy in subcortical MRI segmentation.
UNesT: Local spatial representation learning with hierar- chical transformer for efficient medical segmentation
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Automatic Landmark-Based Segmentation of Human Subcortical Structures in MRI
A three-stage pipeline detects 16 landmarks, coarsely segments 12 labels, and refines them into 26 structures using landmark constraints to improve accuracy in subcortical MRI segmentation.