FetalSurfer: Automated Fetal Cortical Surface Reconstruction

Motivation: The cerebral cortex of the fetus is undergoing intricate development. Abnormal cortical development may potentially alter brain function. However the methods for processing fetal MRI images, especially cortical reconstruction, are still far behind those used for adults. Goal(s): To develop an accurate cortical surface reconstruction method and perform morphological calculations for fetal MRI. Approach: Trustworthy AI segmentation and refined Freesurfer were used to process T2-weighted fetal brain image. Results: The proposed mothod (FetalSurfer) allows for trustworthy reconstruction of the cortical surfaces of the fetal brain and calculation of indicators to measure the morphology of fetal development. Impact: FetalSurfer implements a novel fetal cerebral cortex reconstruction method without manual refinement by professional doctors, filling the gap of fetal image processing methods. Calculated indicators as curvature, thickness and sulcal depth can be used to perform morphological analysis.