Semi-Supervised Multi-Organ Segmentation via Deep Multi-Planar Co-Training

Understand

In multi-organ segmentation of abdominal CT scans, most existing fully supervised deep learning algorithms require lots of voxel-wise annotations, which are usually difficult, expensive, and slow to obtain.

• In comparison, massive unlabeled 3D CT volumes are usually easily accessible.
• Current mainstream works to address the semi-supervised biomedical image segmentation problem are mostly graph-based.
• By contrast, deep network based semi-supervised learning methods have not drawn much attention in this field.