Fetal brain tissue annotation and segmentation challenge results

Kelly Payette, Hongwei Bran Li, Priscille de Dumast, Roxane Licandro, Hui Ji, Md Mahfuzur Rahman Siddiquee, Daguang Xu, Andriy Myronenko, Hao Liu, Yuchen Pei, Lisheng Wang, Ying Peng, Juanying Xie, Huiquan Zhang, Guiming Dong, Hao Fu, Guotai Wang, ZunHyan Rieu, Donghyeon Kim, Hyun Gi Kim et al. (38 additional authors not shown)

Abstract: Highlights•Benchmark for future automatic multi-tissue fetal brain segmentation algorithms.•Used the largest publicly available fetal brain dataset with manual annotations.•U-Net is the dominant method for automatic fetal brain segmentation.•Results using the U-Net have reached a plateau.•Challenge results analyzed from both technical and clinical perspectives.