output
20172026
most citedSynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth

239 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2017 · cs.CVShow all

2 papers · 2 filters

cs.CV2017★ 11 cited

Adversarial Synthesis Learning Enables Segmentation Without Target Modality Ground Truth

Yuankai Huo, Zhoubing Xu, Shunxing Bao +3

A lack of generalizability is one key limitation of deep learning based segmentation. Typically, one manually labels new training images when segmenting organs in different imaging…

cs.CV2017★ 8 cited

Splenomegaly Segmentation using Global Convolutional Kernels and Conditional Generative Adversarial Networks

Yuankai Huo, Zhoubing Xu, Shunxing Bao +7

Spleen volume estimation using automated image segmentation technique may be used to detect splenomegaly (abnormally enlarged spleen) on Magnetic Resonance Imaging (MRI) scans. In…