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Automated segmentation of intracranial hemorrhages from 3D CT

Authors :
Siddiquee, Md Mahfuzur Rahman
Yang, Dong
He, Yufan
Xu, Daguang
Myronenko, Andriy
Publication Year :
2022

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.<br />Comment: INSTANCE22 challenge report, MICCAI2022. arXiv admin note: substantial text overlap with arXiv:2209.09546

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2209.10648
Document Type :
Working Paper