Contouring by Unit Vector Field Regression
Amir Jamaludin Sarim Ather Timor Kadir Rhydian Windsor
This work introduces a simple deep-learning based method to delineate
contours by `walking' along learnt unit vector fields. We demonstrate the
effectiveness of our pipeline on the unique case of open contours on the task
of delineating the sacroiliac joints (SIJs) in spinal MRIs. We show that: (i)
95% of the time the average root mean square error of the predicted contour
against the original ground truth is below 4.5 pixels (2.5mm for a standard
T1-weighted SIJ MRI), and (ii) the proposed method is better than the baseline
of regressing vertices or landmarks of contours.