@inproceedings{4c16ddc7855e4bf283abdf336b665a6e,
title = "Interwound Structural and Functional Difference Between Preterm and Term Infant Brains Revealed by Multi-view CCA",
abstract = "The perinatal period is a critical time of development of brain cortex, structural connection and function. Therefore, A premature exposure to the extrauterine environment is suggested to have the downstream consequences of abnormality in brain structure, function and cognition. A comparative study between the preterm infant brains and term ones at the term-equivalent age provides a valuable window to investigate the normal and abnormal developmental mechanism of these interwound developmental processes. Most of works focused only on one of these processes, and very few studies are found to interpret how these processes interact with each other and how such interactions have been altered on preterm infants{\textquoteright} brains. To fill this gap, we propose a multi-view canonical correlation analysis (CCA) method with the locality preserving projection (LPP) constraint and the age regression constraint, by which interactions between these interwound structural and functional features are identified to maximize the discrimination between preterm and term groups. Our findings on the interaction patterns among structural and functional features find supports from previous reports and provide new knowledge to the development patterns of infant brains.",
keywords = "Locality preserving projection, Multi-view CCA, Preterm",
author = "Zhibin He and Shu Zhang and Songyao Zhang and Yin Zhang and Xintao Hu and Xi Jiang and Lei Guo and Tianming Liu and Lei Du and Tuo Zhang",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 11th International Workshop on Machine Learning in Medical Imaging, MLMI 2020, held in conjunction with the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2020 ; Conference date: 04-10-2020 Through 04-10-2020",
year = "2020",
doi = "10.1007/978-3-030-59861-7_47",
language = "英语",
isbn = "9783030598600",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "465--473",
editor = "Mingxia Liu and Chunfeng Lian and Pingkun Yan and Xiaohuan Cao",
booktitle = "Machine Learning in Medical Imaging - 11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Proceedings",
}