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HACA3: A Unified Approach for Multi-site MR Image Harmonization
Lianrui Zuo, Yihao Liu, Yuan Xue +10
The lack of standardization is a prominent issue in magnetic resonance (MR) imaging. This often causes undesired contrast variations in the acquired images due to differences in ha…
On Finite Difference Jacobian Computation in Deformable Image Registration
Yihao Liu, Junyu Chen, Shuwen Wei +2
Producing spatial transformations that are diffeomorphic is a key goal in deformable image registration. As a diffeomorphic transformation should have positive Jacobian determinant…
Cross-identity Video Motion Retargeting with Joint Transformation and Synthesis
Haomiao Ni, Yihao Liu, Sharon X. Huang +1
In this paper, we propose a novel dual-branch Transformation-Synthesis network (TS-Net), for video motion retargeting. Given one subject video and one driving video, TS-Net can pro…
CP3: Unifying Point Cloud Completion by Pretrain-Prompt-Predict Paradigm
Mingye Xu, Yali Wang, Yihao Liu +2
Point cloud completion aims to predict complete shape from its partial observation. Current approaches mainly consist of generation and refinement stages in a coarse-to-fine style.…
Disentangling A Single MR Modality
Lianrui Zuo, Yihao Liu, Yuan Xue +5
Disentangling anatomical and contrast information from medical images has gained attention recently, demonstrating benefits for various image analysis tasks. Current methods learn…
A Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Bounds
Wenlong Zhang, Guangyuan Shi, Yihao Liu +2
Degradation models play an important role in Blind super-resolution (SR). The classical degradation model, which mainly involves blur degradation, is too simple to simulate real-wo…
Evaluating the Generalization Ability of Super-Resolution Networks
Yihao Liu, Hengyuan Zhao, Jinjin Gu +2
Performance and generalization ability are two important aspects to evaluate the deep learning models. However, research on the generalization ability of Super-Resolution (SR) netw…
Coordinate Translator for Learning Deformable Medical Image Registration
Yihao Liu, Lianrui Zuo, Shuo Han +3
The majority of deep learning (DL) based deformable image registration methods use convolutional neural networks (CNNs) to estimate displacement fields from pairs of moving and fix…