Title
Towards Accurate And Robust Multi-Modal Medical Image Registration Using Contrastive Metric Learning
Abstract
Multi-modal medical image registration takes an essential role in image-based clinical diagnosis and surgical planning. It is not trivial due to appearance variations across different modalities. Rigidly aligning two images is used to register rigid body structure, and it is also usually the first step for deformable registration with a large discrepancy. In the field of computer vision, one well-established method for image alignment is to find corresponding points from two images, and image alignment is based on identified corresponding points. Our method lies in this category. Feature representation is crucial in finding corresponding points. However, conventional feature representation like SIFT does not take multi-modal information into account, and thus, it fails. In this paper, we propose a Convolution Neural Network Feature-based Registration (CNNFR) method for aligning the multi-modal medical image. The important component in this method is learning keypoint descriptors using contrastive metric learning, which minimizes the difference between two feature representations from two corresponding points and maximizes difference of two feature representation from two distant points. Also, a transfer learning-based CNNRF (TrCNNRF) is proposed to improve the generalization learning performance when the training data are insufficient. Experimental results demonstrate that the proposed methods can achieve superior performance regarding both accuracy and robustness, which can be used to rigidly register multi-modal images and provide an initial estimation for non-rigid registration in clinical practices.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2938858
IEEE ACCESS
Keywords
DocType
Volume
Medical image registration, convolution neural networks (CNNs), transfer learning, feature descriptor, contrastive metric learning
Journal
7
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
11
Name
Order
Citations
PageRank
Jinrong Hu163.16
Shanhui Sun29511.82
Xiaodong Yang300.34
Shuang Zhou400.34
Xin Wang57412.92
Ying Fu601.69
Jiliu Zhou745058.21
Youbing Yin84410.98
Kunlin Cao900.68
Qi Song10177.87
Xi Wu116118.90