25 citations · 47 across the 6 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
cs.CV2019★ 2 cited
VoteNet+ : An Improved Deep Learning Label Fusion Method for Multi-atlas Segmentation
Zhipeng Ding, Xu Han, Marc Niethammer
In this work, we improve the performance of multi-atlas segmentation (MAS) by integrating the recently proposed VoteNet model with the joint label fusion (JLF) approach. Specifical…
cs.CV2019★ 7 cited
VoteNet: A Deep Learning Label Fusion Method for Multi-Atlas Segmentation
Zhipeng Ding, Xu Han, Marc Niethammer
Deep learning (DL) approaches are state-of-the-art for many medical image segmentation tasks. They offer a number of advantages: they can be trained for specific tasks, computation…
cs.CV2019★ 11 cited
Networks for Joint Affine and Non-parametric Image Registration
Zhengyang Shen, Xu Han, Zhenlin Xu +1
We introduce an end-to-end deep-learning framework for 3D medical image registration. In contrast to existing approaches, our framework combines two registration methods: an affine…