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Mapping fetal brain development based on automated segmentation and 4D brain atlasing

Abstract

Fetal brain MRI has become an important tool for in utero assessment of brain development and disorders. However, quantitative analysis of fetal brain MRI remains difficult, partially due to the limited tools for automated preprocessing and the lack of normative brain templates. In this paper, we proposed an automated pipeline for fetal brain extraction, super-resolution reconstruction, and fetal brain atlasing to quantitatively map in utero fetal brain development during mid-to-late gestation in a Chinese population. First, we designed a U-net convolutional neural network for automated fetal brain extraction, which achieved an average accuracy of 97%. We then generated a developing fetal brain atlas, using an iterative linear and nonlinear registration approach. Based on the 4D spatiotemporal atlas, we quantified the morphological development of the fetal brain between 23 and 36 weeks of gestation. The proposed pipeline enabled the fully automated volumetric reconstruction for clinically available fetal brain MRI data, and the 4D fetal brain atlas provided normative templates for the quantitative characterization of fetal brain development, especially in the Chinese population.

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Availability of data and material

The data (anonymized) in this study can be accessed with a data-sharing agreement.

Code availability

The code used in this work is available from the authors upon request.

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Funding

This work was supported by the Ministry of Science and Technology of the People’s Republic of China (2018YFE0114600), National Natural Science Foundation of China (61801424, 81971606, 61801421, and 81971605), and the Leading Innovation and Entrepreneurship Team of Zhejiang Province (202006140).

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HL: processed MRI data and performed analyses. DW: was in charge of the study design and overall progress of the study. HL and DW: drafted the manuscript. GY, KL, and YZ: contributed to the collection of the MRI data. All authors contributed to the interpretation and review of the manuscript.

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Correspondence to Dan Wu.

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Li, H., Yan, G., Luo, W. et al. Mapping fetal brain development based on automated segmentation and 4D brain atlasing. Brain Struct Funct 226, 1961–1972 (2021). https://doi.org/10.1007/s00429-021-02303-x

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Keywords

  • U-net convolutional network
  • Fetal brain extraction
  • Chinese fetal brain atlas
  • Morphological development
  • Super-resolution reconstruction