Abstract #0076

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

Haotian Li¹, Guohui Yan², Wanrong Luo¹, Tingting Liu¹, Yan Wang¹, Yi Zhang¹, Li Zhao³, Catherine Limperopoulos³, Yu Zou², and Dan Wu¹

¹Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China, ²Department of Radiology, Women's Hospital,School of Medicine,Zhejiang University, Hangzhou, Zhejiang, China, ³Diagnostic Imaging and Radiology, Children's National Medical Center, Washington, DC, WA, United States

Fetal brain MRI has become an important tool for in-utero assessment of brain development and disorders. Here we proposed an automated pipeline with fetal brain segmentation, super-resolution reconstruction, and fetal brain atlasing to quantitatively map in-utero fetal brain development in a Chinese population. We designed a U-net CNN implemented for automatic fetal brain segmentation, which showed superior segmentation accuracy compared with conventional methods. We then generated a Chinese fetal brain atlas, using an iterative linear and nonlinear registration method. Based on the 4D spatiotemporal atlas, we characterized the three-dimensional morphological evolution of the fetal brain between 23-36 weeks of gestation.

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