7 citations · 12 across the 5 of their papers we have counts for
6 papers
Aladdin: Joint Atlas Building and Diffeomorphic Registration Learning with Pairwise Alignment
Zhipeng Ding, Marc Niethammer
Atlas building and image registration are important tasks for medical image analysis. Once one or multiple atlases from an image population have been constructed, commonly (1) imag…
VoteNet++: Registration Refinement for Multi-Atlas Segmentation
Zhipeng Ding, Marc Niethammer
Multi-atlas segmentation (MAS) is a popular image segmentation technique for medical images. In this work, we improve the performance of MAS by correcting registration errors befor…
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…
Fast Predictive Simple Geodesic Regression
Zhipeng Ding, Greg Fleishman, Xiao Yang +3
Deformable image registration and regression are important tasks in medical image analysis. However, they are computationally expensive, especially when analyzing large-scale datas…