58 citations · 101 across the 22 of their papers we have counts for
6 papers · 1 filter
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…
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…
F3RNet: Full-Resolution Residual Registration Network for Deformable Image Registration
Zhe Xu, Jie Luo, Jiangpeng Yan +2
Deformable image registration (DIR) is essential for many image-guided therapies. Recently, deep learning approaches have gained substantial popularity and success in DIR. Most dee…
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…
Do Public Datasets Assure Unbiased Comparisons for Registration Evaluation?
Jie Luo, Guangshen Ma, Sarah Frisken +8
With the increasing availability of new image registration approaches, an unbiased evaluation is becoming more needed so that clinicians can choose the most suitable approaches for…
An Investigation of Feature-based Nonrigid Image Registration using Gaussian Process
Siming Bayer, Ute Spiske, Jie Luo +8
For a wide range of clinical applications, such as adaptive treatment planning or intraoperative image update, feature-based deformable registration (FDR) approaches are widely emp…