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ShanghaiTech University Knowledge Management System
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]) |
ISSN | 0302-9743 |
卷号 | 14349 LNCS |
页码 | 467-475 |
发表状态 | 已发表 |
DOI | 10.1007/978-3-031-45676-3_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 |
EISSN | 1611-3349 |
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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