An end‐to‐end infant brain parcellation pipeline  

作　　者：Limei Wang Yue Sun Weili Lin Gang Li Li Wang 

机构地区：[1]Department of Radiology and Biomedical Research Imaging Center,UNC-Chapel Hill,New Caledonia,27599,USA

出　　处：《Intelligent Medicine》2024年第2期65-74,共10页智慧医学（英文）

基　　金：funded by National Institutes of Health(Grant Nos.MH117943,MH109773,MH116225,and MH123202);Additionally,the work leverages approaches developed through an National Institutes of Health(Grant No.1U01MH110274);the efforts of the Baby Connectome Project Consortium at UNC/UMIN.

摘　　要：Objective Accurate infant brain parcellation is crucial for understanding early brain development;however,it is challenging due to the inherent low tissue contrast,high noise,and severe partial volume effects in infant magnetic resonance images(MRIs).The aim of this study was to develop an end-to-end pipeline that enabled accurate parcellation of infant brain MRIs.Methods We proposed an end-to-end pipeline that employs a two-stage global-to-local approach for accurate parcellation of infant brain MRIs.Specifically,in the global regions of interest(ROIs)localization stage,a combination of transformer and convolution operations was employed to capture both global spatial features and fine texture features,enabling an approximate localization of the ROIs across the whole brain.In the local ROIs refinement stage,leveraging the position priors from the first stage along with the raw MRIs,the boundaries of the ROIs are refined for a more accurate parcellation.Results We utilized the Dice ratio to evaluate the accuracy of parcellation results.Results on 263 subjects from National Database for Autism Research(NDAR),Baby Connectome Project(BCP)and Cross-site datasets demonstrated the better accuracy and robustness of our method than other competing methods.Conclusion Our end-to-end pipeline may be capable of accurately parcellating 6-month-old infant brain MRIs.

关 键 词：Infant brain parcellation Isointense magnetic resonance image Convolutional neural networks TRANSFORMER 

分 类 号：R72[医药卫生—儿科] TP183[医药卫生—临床医学]