25 citations · 47 across the 6 of their papers we have counts for
7 papers
A Deep Network for Joint Registration and Reconstruction of Images with Pathologies
Xu Han, Zhengyang Shen, Zhenlin Xu +5
Registration of images with pathologies is challenging due to tissue appearance changes and missing correspondences caused by the pathologies. Moreover, mass effects as observed fo…
Local Temperature Scaling for Probability Calibration
Zhipeng Ding, Xu Han, Peirong Liu +1
For semantic segmentation, label probabilities are often uncalibrated as they are typically only the by-product of a segmentation task. Intersection over Union (IoU) and Dice score…
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…
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…
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…
Brain Extraction from Normal and Pathological Images: A Joint PCA/Image-Reconstruction Approach
Xu Han, Roland Kwitt, Stephen Aylward +6
Brain extraction from images is a common pre-processing step. Many approaches exist, but they are frequently only designed to perform brain extraction from images without strong pa…