Abstract #0238

Harmonizing Multi-Modality Biases in Infant Development Analysis with an Integrated MRI Data Processing Pipeline

Feihong Liu^1,2, Jiawei Huang¹, Lianghu Guo¹, Haifeng Tang¹, Xinyi Cai¹, Yajuan Zhang¹, Jiameng Liu¹, Rui Hua³, Jinchen Gu¹, Tianli Tao¹, Zhongrui Huang¹, Yichu He³, Zehong Cao³, Luoyu Wang¹, Xuyun Wen⁴, Geng Chen⁵, Fan Wang⁶, Chunfeng Lian⁷, Feng Shi³, Qian Wang^1,8, Jun Feng², Han Zhang^1,8, and Dinggang Shen^1,3,8

¹School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China, ²School of Information and Technology, Northwest University, Xi'an, China, ³Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China, ⁴Department of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics, Nanjing, China, ⁵School of Computer Science and Engineering, Northwestern Polytechnical Universit, Xi'an, China, ⁶The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi’an Jiaotong University, Xi'an, China, ⁷School of Mathematics and Statistics, Xi’an Jiaotong University, Xi'an, China, ⁸Shanghai Clinical Research and Trial Center, Shanghai, China

Synopsis

Keywords: Data Processing, Brain, Neuroimage computing，pipeline

Motivation: Understanding infant neurodevelopment is pivotal for unraveling the anatomical underpinnings of psychomotor and cognitive functions, as well as pinpointing the origins of various disorders.

Goal(s): Introduce an integrated multi-modality MRI data processing pipeline tailored for infant development studies, with the goal of reliablly discerning relationship across brain anatomy and cognitive functions.

Approach: Incorporating precise deep learning tools specifically designed for infant brain, structural, functional, diffusion MRI data can be accurately analyzed, w.r.t. surface attributes for group-level study and network attributes for individual-level study.

Results: We introduce an integrated multi-modal infant MRI data processing pipeline toolkit with dedicated processing results.

Impact: We introduce the first infant multi-modal atlas and parcellation map

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