Attention-gated U-Net networks for simultaneous axial/sagittal planes segmentation of injured spinal cords.

Magnetic resonance imaging is currently the gold standard for the evaluation of spinal cord injuries. Automatic analysis of these injuries is however challenging, as MRI resolutions vary for different planes of analysis and physiological features are often distorted around these injuries. This study proposes a new CNN-based segmentation method in which information is exchanged between two networks analyzing the scans from different planes.