A subject-specific unsupervised deep learning method for quantitative susceptibility mapping using implicit neural representation

•Subject-specific and unsupervised deep learning for QSM reconstruction.•Integration of implicit continuous signal representation and explicit regularizations.•Phase compensation strategy for an accurate physical model.•Improved accuracy and quality compared with established methods. Quantitative su...

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Bibliographic Details

Published in:	Medical image analysis Vol. 95; p. 103173
Main Authors:	Zhang, Ming, Feng, Ruimin, Li, Zhenghao, Feng, Jie, Wu, Qing, Zhang, Zhiyong, Ma, Chengxin, Wu, Jinsong, Yan, Fuhua, Liu, Chunlei, Zhang, Yuyao, Wei, Hongjiang
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 01.07.2024
Subjects:	Implicit neural representation Phase compensation Quantitative susceptibility mapping Unsupervised learning Quantitative susceptibility mapping Implicit neural representation Unsupervised learning Phase compensation
ISSN:	1361-8415, 1361-8423, 1361-8423
Online Access:	Get full text
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