Unsupervised Imbalanced Registration for Enhancing Accuracy and Stability in Medical Image Registration

Title:Unsupervised Imbalanced Registration for Enhancing Accuracy and Stability in Medical Image Registration

Volume: 20

Author(s): Peizhi Chen*, Jiacheng Lin, Yifan Guo and Xuan Pei

Affiliation:

• College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China
• Key Laboratory of Pattern Recognition and Image Understanding, Fujian, Xiamen 361024, China

Keywords: Unsupervised imbalanced registration, Unsupervised image mixtures, Data imbalance, 4d-Lung, Medical image registration, Continuous variable.

Abstract:

Background: Medical image registration plays an important role in several applications. Existing approaches using unsupervised learning encounter issues due to the data imbalance problem, as their target is usually a continuous variable.

Objective: In this study, we introduce a novel approach known as Unsupervised Imbalanced Registration, to address the challenge of data imbalance and prevent overconfidence while increasing the accuracy and stability of 4D image registration.

Methods: Our approach involves performing unsupervised image mixtures to smooth the input space, followed by unsupervised image registration to learn the continual target. We evaluated our method on 4D-Lung using two widely used unsupervised methods, namely VoxelMorph and ViT-V-Net.

Results: Our findings demonstrate that our proposed method significantly enhances the mean accuracy of registration by 3%-10% on a small dataset while also reducing the accuracy variance by 10%.

Conclusion: Unsupervised Imbalanced Registration is a promising approach that is compatible with current unsupervised image registration methods applied to 4D images.

Cite this article as:

Chen Peizhi*, Lin Jiacheng, Guo Yifan and Pei Xuan, Unsupervised Imbalanced Registration for Enhancing Accuracy and Stability in Medical Image Registration, Current Medical Imaging 2024; 20 : e15734056265001 . https://dx.doi.org/10.2174/0115734056265001231122110350