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20232025
most citedEncoder-Only Image Registration

4 citations · 6 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025★ 4 cited

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2024

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…