activity
20192022
most citedNetworks for Joint Affine and Non-parametric Image Registration

11 citations · 18 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG20223 cited

Compositional Generalization in Unsupervised Compositional Representation Learning: A Study on Disentanglement and Emergent Language

Zhenlin Xu, Marc Niethammer, Colin Raffel

Deep learning models struggle with compositional generalization, i.e. the ability to recognize or generate novel combinations of observed elementary concepts. In hopes of enabling…

eess.IV20202 cited

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…

cs.CV20202 cited

Anatomical Data Augmentation via Fluid-based Image Registration

Zhengyang Shen, Zhenlin Xu, Sahin Olut +1

We introduce a fluid-based image augmentation method for medical image analysis. In contrast to existing methods, our framework generates anatomically meaningful images via interpo…

cs.CV2019

DeepAtlas: Joint Semi-Supervised Learning of Image Registration and Segmentation

Zhenlin Xu, Marc Niethammer

Deep convolutional neural networks (CNNs) are state-of-the-art for semantic image segmentation, but typically require many labeled training samples. Obtaining 3D segmentations of m…

cs.CV201911 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…