4 citations · 6 across the 11 of their papers we have counts for
11 papers
Encoder-Only Image Registration
Xiang Chen, Renjiu Hu, Jinwei Zhang +5
Learning-based techniques have significantly improved the accuracy and speed of deformable image registration. However, challenges such as reducing computational complexity and han…
Gaussian Primitive Optimized Deformable Retinal Image Registration
Xin Tian, Jiazheng Wang, Yuxi Zhang +5
Deformable retinal image registration is notoriously difficult due to large homogeneous regions and sparse but critical vascular features, which cause limited gradient signals in s…
VoxelOpt: Voxel-Adaptive Message Passing for Discrete Optimization in Deformable Abdominal CT Registration
Hang Zhang, Yuxi Zhang, Jiazheng Wang +5
Recent developments in neural networks have improved deformable image registration (DIR) by amortizing iterative optimization, enabling fast and accurate DIR results. However, lear…
Unsupervised Deformable Image Registration with Structural Nonparametric Smoothing
Hang Zhang, Xiang Chen, Renjiu Hu +7
Learning-based deformable image registration (DIR) accelerates alignment by amortizing traditional optimization via neural networks. Label supervision further enhances accuracy, en…
Fidelity-Imposed Displacement Editing for the Learn2Reg 2024 SHG-BF Challenge
Jiacheng Wang, Xiang Chen, Renjiu Hu +5
Co-examination of second-harmonic generation (SHG) and bright-field (BF) microscopy enables the differentiation of tissue components and collagen fibers, aiding the analysis of hum…
Large Scale Unsupervised Brain MRI Image Registration Solution for Learn2Reg 2024
Yuxi Zhang, Xiang Chen, Jiazheng Wang +5
In this paper, we summarize the methods and experimental results we proposed for Task 2 in the learn2reg 2024 Challenge. This task focuses on unsupervised registration of anatomica…
MemWarp: Discontinuity-Preserving Cardiac Registration with Memorized Anatomical Filters
Hang Zhang, Xiang Chen, Renjiu Hu +3
Many existing learning-based deformable image registration methods impose constraints on deformation fields to ensure they are globally smooth and continuous. However, this assumpt…
Slicer Networks
Hang Zhang, Xiang Chen, Rongguang Wang +3
In medical imaging, scans often reveal objects with varied contrasts but consistent internal intensities or textures. This characteristic enables the use of low-frequency approxima…
RimSet: Quantitatively Identifying and Characterizing Chronic Active Multiple Sclerosis Lesion on Quantitative Susceptibility Maps
Jinwei Zhang, Thanh D. Nguyen, Renjiu Hu +3
Background: Rim+ lesions in multiple sclerosis (MS), detectable via Quantitative Susceptibility Mapping (QSM), correlate with increased disability. Existing literature lacks quanti…
Multi-delay arterial spin-labeled perfusion estimation with biophysics simulation and deep learning
Renjiu Hu, Qihao Zhang, Pascal Spincemaille +2
Purpose: To develop biophysics-based method for estimating perfusion Q from arterial spin labeling (ASL) images using deep learning. Methods: A 3D U-Net (QTMnet) was trained to est…
Spatially Covariant Image Registration with Text Prompts
Xiang Chen, Min Liu, Rongguang Wang +4
Medical images are often characterized by their structured anatomical representations and spatially inhomogeneous contrasts. Leveraging anatomical priors in neural networks can gre…