Imperial College London
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DR BERNHARD KAINZ

Faculty of Engineering, Department of Computing

Reader in Medical Image Computing
 
 
 
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Contact

 

+44 (0)20 7594 8349b.kainz Website CV

 
 
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Location

 

372Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Li:2021:10.1007/978-3-030-87735-4_21,
author = {Li, L and Sinclair, M and Makropoulos, A and Hajnal, JV and David, Edwards A and Kainz, B and Rueckert, D and Alansary, A},
doi = {10.1007/978-3-030-87735-4_21},
pages = {221--230},
publisher = {Springer},
title = {CAS-Net: Conditional atlas generation and brain segmentation for fetal MRI},
url = {http://dx.doi.org/10.1007/978-3-030-87735-4_21},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Fetal Magnetic Resonance Imaging (MRI) is used in prenatal diagnosis and to assess early brain development. Accurate segmentation of the different brain tissues is a vital step in several brain analysis tasks, such as cortical surface reconstruction and tissue thickness measurements. Fetal MRI scans, however, are prone to motion artifacts that can affect the correctness of both manual and automatic segmentation techniques. In this paper, we propose a novel network structure that can simultaneously generate conditional atlases and predict brain tissue segmentation, called CAS-Net. The conditional atlases provide anatomical priors that can constrain the segmentation connectivity, despite the heterogeneity of intensity values caused by motion or partial volume effects. The proposed method is trained and evaluated on 253 subjects from the developing Human Connectome Project (dHCP). The results demonstrate that the proposed method can generate conditional age-specific atlas with sharp boundary and shape variance. It also segment multi-category brain tissues for fetal MRI with a high overall Dice similarity coefficient (DSC) of 85.2% for the selected 9 tissue labels.
AU  - Li,L
AU  - Sinclair,M
AU  - Makropoulos,A
AU  - Hajnal,JV
AU  - David,Edwards A
AU  - Kainz,B
AU  - Rueckert,D
AU  - Alansary,A
DO  - 10.1007/978-3-030-87735-4_21
EP  - 230
PB  - Springer
PY  - 2021///
SN  - 0302-9743
SP  - 221
TI  - CAS-Net: Conditional atlas generation and brain segmentation for fetal MRI
UR  - http://dx.doi.org/10.1007/978-3-030-87735-4_21
UR  - http://hdl.handle.net/10044/1/96917
ER  -
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