English

Automated segmentation of intracranial hemorrhages from 3D CT

Image and Video Processing 2022-09-23 v1 Computer Vision and Pattern Recognition

Abstract

Intracranial hemorrhage segmentation challenge (INSTANCE 2022) offers a platform for researchers to compare their solutions to segmentation of hemorrhage stroke regions from 3D CTs. In this work, we describe our solution to INSTANCE 2022. We use a 2D segmentation network, SegResNet from MONAI, operating slice-wise without resampling. The final submission is an ensemble of 18 models. Our solution (team name NVAUTO) achieves the top place in terms of Dice metric (0.721), and overall rank 2. It is implemented with Auto3DSeg.

Keywords

Cite

@article{arxiv.2209.10648,
  title  = {Automated segmentation of intracranial hemorrhages from 3D CT},
  author = {Md Mahfuzur Rahman Siddiquee and Dong Yang and Yufan He and Daguang Xu and Andriy Myronenko},
  journal= {arXiv preprint arXiv:2209.10648},
  year   = {2022}
}

Comments

INSTANCE22 challenge report, MICCAI2022. arXiv admin note: substantial text overlap with arXiv:2209.09546