Contouring by Unit Vector Field Regression

Amir Jamaludin, Sarim Ather, Timor Kadir, Rhydian Windsor
5/26/2023
cs.CV

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Abstract

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.

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Cite this paper

@article{jamaludin2023contouring,
  title  = {Contouring by Unit Vector Field Regression},
  author = {Amir Jamaludin and Sarim Ather and Timor Kadir and Rhydian Windsor},
  year   = {2023},
  eprint = {2305.17024},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2305.17024v1}
}

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