C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation

CVPR 2020 Qihang YuDong YangHolger RothYutong BaiYixiao ZhangAlan L. YuilleDaguang Xu

3D convolution neural networks (CNN) have been proved very successful in parsing organs or tumours in 3D medical images, but it remains sophisticated and time-consuming to choose or design proper 3D networks given different task contexts. Recently, Neural Architecture Search (NAS) is proposed to solve this problem by searching for the best network architecture automatically... (read more)

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