English

MixMicrobleed: Multi-stage detection and segmentation of cerebral microbleeds

Image and Video Processing 2021-08-29 v1 Computer Vision and Pattern Recognition

Abstract

Cerebral microbleeds are small, dark, round lesions that can be visualised on T2*-weighted MRI or other sequences sensitive to susceptibility effects. In this work, we propose a multi-stage approach to both microbleed detection and segmentation. First, possible microbleed locations are detected with a Mask R-CNN technique. Second, at each possible microbleed location, a simple U-Net performs the final segmentation. This work used the 72 subjects as training data provided by the "Where is VALDO?" challenge of MICCAI 2021.

Keywords

Cite

@article{arxiv.2108.02482,
  title  = {MixMicrobleed: Multi-stage detection and segmentation of cerebral microbleeds},
  author = {Marta Girones Sanguesa and Denis Kutnar and Bas H. M. van der Velden and Hugo J. Kuijf},
  journal= {arXiv preprint arXiv:2108.02482},
  year   = {2021}
}

Comments

Submitted to the "Where is VALDO?" challenge, MICCAI 2021

R2 v1 2026-06-24T04:51:08.358Z