Meeting Banner
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.

This abstract and the presentation materials are available to 2020 meeting attendees and eLibrary customers only; a login is required.

Join Here