Abstract #4094

The development of automatic 3D fetal brain MRI analysis methods for depicting growth trajectories of fetal brain tissues

YISHAN LUO^1,2, LIN SHI^3,4,5, DANTONG MIAO⁶, XIN ZHANG⁶, Queenie Chan⁷, Winnie CW CHU¹, BING ZHANG⁶, and DEFENG WANG^1,8

¹Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, Hong Kong, ²Shenzhen Research Institute,The Chinese University of Hong Kong, Shenzhen, People's Republic of China, ³Chow Yuk Ho Technology Center for Innovative Medicine, Hong Kong, ⁴Therese Pei Fong Chow Research Centre for Prevention of Dementia, ⁵Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, ⁶Department of Radiology, Nanjing Drum Tower Hospital,The Affiliated Hospital of Nanjing University Medical School, Nanjing, People's Republic of China, ⁷Philips Healthcare, Hong Kong, ⁸Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, People's Republic of China

In this paper, we proposed a set of fetal brain MRI analysis methods to quantify the fetal brain tissue volume. We used deep learning-based brain mask extraction method to obtain brain mask and reconstructed 3D fetal brain volumes using registration-based reconstruction method. Then an age-specific atlas-based segmentation method was applied to segment three major tissues (White Matter, cortical Gray Matter, cerebrospinal fluid). The changes of intracranial volume and the three brain tissue volumes across different gestational ages were calculated and fitted with both linear and quadratic curves. The results demonstrated the effectiveness of the automatic 3D fetal MRI quantification methods.

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