Automated segmentation of intracranial hemorrhages from 3D CT
- URL: http://arxiv.org/abs/2209.10648v1
- Date: Wed, 21 Sep 2022 20:37:32 GMT
- Title: Automated segmentation of intracranial hemorrhages from 3D CT
- Authors: Md Mahfuzur Rahman Siddiquee, Dong Yang, Yufan He, Daguang Xu, Andriy
Myronenko
- Abstract summary: Intracranial hemorrhage segmentation challenge (INSTANCE 2022) offers a platform for researchers to compare their solutions to segmentation of hemorrhage stroke regions from 3D CTs.
We use a 2D segmentation network, SegResNet from MONAI, operating slice-wise without resampling.
- Score: 9.814838162752114
- License: http://creativecommons.org/licenses/by/4.0/
- 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.
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