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Regionalized Infant Brain Cortical Development Based on Multi-view, High-Level fMRI Fingerprint
2023-10-08
会议录名称INTERNATIONAL WORKSHOP ON MACHINE LEARNING IN MEDICAL IMAGING (IF:0.402[JCR-2005],0.000[5-Year])
ISSN0302-9743
卷号14349 LNCS
页码467-475
发表状态已发表
DOI10.1007/978-3-031-45676-3_47
摘要

The human brain demonstrates higher spatial and functional heterogeneity during the first two postnatal years than any other period of life. Infant cortical developmental regionalization is fundamental for illustrating brain microstructures and reflecting functional heterogeneity during early postnatal brain development. It aims to establish smooth cortical parcellations based on the local homogeneity of brain development. Therefore, charting infant cortical developmental regionalization can reveal neurodevelopmentally meaningful cortical units and advance our understanding of early brain structural and functional development. However, existing parcellations are solely built based on either local structural properties or single-view functional connectivity (FC) patterns due to limitations in neuroimage analysis tools. These approaches fail to capture the diverse consistency of local and global functional development. Hence, we aim to construct a multi-view functional brain parcellation atlas, enabling a better understanding of infant brain functional organization during early development. Specifically, a novel fMRI fingerprint is proposed to fuse complementary regional functional connectivities. To ensure the smoothness and interpretability of the discovered map, we employ non-negative matrix factorization (NNMF) with dual graph regularization in our method. Our method was validated on the Baby Connectome Project (BCP) dataset, demonstrating superior performance compared to previous functional and structural parcellation approaches. Furthermore, we track functional development trajectory based on our brain cortical parcellation to highlight early development with high neuroanatomical and functional precision. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

会议举办国中国
关键词Functional neuroimaging Non-negative matrix factorization Brain atlas Brain chart Brain development Brain parcellation Connectomes Functional connectome Functional heterogeneity Infant brain development Multi-views Regionalisation
会议名称14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023
会议地点Vancouver, BC, Canada
会议日期October 8, 2023 - October 8, 2023
收录类别EI
语种英语
出版者Springer Science and Business Media Deutschland GmbH
EI入藏号20234515039009
EI主题词Brain
EISSN1611-3349
EI分类号461.1 Biomedical Engineering ; 746 Imaging Techniques ; 921 Mathematics
原始文献类型Conference article (CA)
文献类型会议论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/345930
专题生物医学工程学院_PI研究组_沈定刚组
信息科学与技术学院_硕士生
生物医学工程学院_PI研究组_张寒组
通讯作者Han Zhang
作者单位
ShanghaiTech University
第一作者单位上海科技大学
通讯作者单位上海科技大学
第一作者的第一单位上海科技大学
推荐引用方式
GB/T 7714
Tao Tianli,Jiawei Huang,Feihong Liu,et al. Regionalized Infant Brain Cortical Development Based on Multi-view, High-Level fMRI Fingerprint[C]:Springer Science and Business Media Deutschland GmbH,2023:467-475.
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