most citedAdversarial Uni- and Multi-modal Stream Networks for Multimodal Image Registration

3 citations · 10 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2020

Unsupervised Multimodal Image Registration with Adaptative Gradient Guidance

Zhe Xu, Jiangpeng Yan, Jie Luo +2

Multimodal image registration (MIR) is a fundamental procedure in many image-guided therapies. Recently, unsupervised learning-based methods have demonstrated promising performance…

cs.CV20203 cited

Unimodal Cyclic Regularization for Training Multimodal Image Registration Networks

Zhe Xu, Jiangpeng Yan, Jie Luo +3

The loss function of an unsupervised multimodal image registration framework has two terms, i.e., a metric for similarity measure and regularization. In the deep learning era, rese…

cs.CV2020

Real-time Dense Reconstruction of Tissue Surface from Stereo Optical Video

Haoyin Zhou, Jagadeesan Jayender

We propose an approach to reconstruct dense three-dimensional (3D) model of tissue surface from stereo optical videos in real-time, the basic idea of which is to first extract 3D i…

cs.CV20202 cited

Re-weighting and 1-Point RANSAC-Based PnP Solution to Handle Outliers

Haoyin Zhou, Tao Zhang, Jagadeesan Jayender

The ability to handle outliers is essential for performing the perspective-n-point (PnP) approach in practical applications, but conventional RANSAC+P3P or P4P methods have high ti…

cs.CV20202 cited

Real-time Surface Deformation Recovery from Stereo Videos

Haoyin Zhou, Jagadeesan Jayender

Tissue deformation during the surgery may significantly decrease the accuracy of surgical navigation systems. In this paper, we propose an approach to estimate the deformation of t…

eess.IV20203 cited

Adversarial Uni- and Multi-modal Stream Networks for Multimodal Image Registration

Zhe Xu, Jie Luo, Jiangpeng Yan +4

Deformable image registration between Computed Tomography (CT) images and Magnetic Resonance (MR) imaging is essential for many image-guided therapies. In this paper, we propose a…