4k citations · 4.2k across the 32 of their papers we have counts for
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cs.CV2019★ 18 cited
C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation
Qihang Yu, Dong Yang, Holger Roth +4
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 o…
cs.CV2019★ 28 cited
Thickened 2D Networks for Efficient 3D Medical Image Segmentation
Qihang Yu, Yingda Xia, Lingxi Xie +2
There has been a debate in 3D medical image segmentation on whether to use 2D or 3D networks, where both pipelines have advantages and disadvantages. 2D methods enjoy a low inferen…