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Whole brain segmentation method from 2.5D brain MRI slice image based on Triple U-Net

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Abstract

With the application of magnetic resonance imaging (MRI) in the diagnosis of brain diseases, MRI has become a powerful tool for clinical neuroimaging analysis, and whole brain segmentation is a very important step of neuroimaging analysis. In order to promote segmentation accuracy, this paper makes full use of the spatial constraint information between adjacent slice of MRI brain image sequence, and combines three consecutive images into one image named 2.5D slice image. Through 2.5D slice image, a triple U-Net-based whole brain segmentation method is proposed, which is composed of one main U-Net and two auxiliary U-Nets. Moreover, this network introduces three auxiliary outputs to provide inter-layer constraints for the final prediction, and uses a multi-auxiliary hybrid loss function based on binary cross-entropy loss and dice loss to optimize the training model. In this paper, a comprehensive comparative experiment is carried out on LPBA40 dataset and IBSR18 dataset. The experimental results show that the dice coefficient, specificity and sensitivity of this method are 98.23%, 99.62% and 98.54%, respectively, on LPBA40 dataset, and 97.01%, 99.45% and 98%, respectively, on IBSR18 dataset. The experiments show that the accuracy of whole brain segmentation is greatly improved by the proposed triple U-Net.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant 61162023, was supported by the Natural Science Foundation of Jiangxi Province, Grant Number 20192BAB205083.

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Authors and Affiliations

  1. School of Measuring and Optical Engineering, Nanchang Hangkong University, Nanchang, 330063, China

    Xingyan Chen, Shaofeng Jiang, Lanting Guo, Zhen Chen & Congxuan Zhang

  2. Key Laboratory of Nondestructive Testing, Ministry of Education, Nanchang Hangkong University (NCHU), Nanchang, 330063, China

    Shaofeng Jiang, Zhen Chen & Congxuan Zhang

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  1. Xingyan Chen
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Correspondence to Shaofeng Jiang.

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Chen, X., Jiang, S., Guo, L. et al. Whole brain segmentation method from 2.5D brain MRI slice image based on Triple U-Net. Vis Comput 39, 255–266 (2023). https://doi.org/10.1007/s00371-021-02326-9

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