Nonrigid Registration Regularized by Shape Information: Application to Atlas Construction of Cardiac CT Images

Yunfei Zha; Xuesong Lu; Li Wang; Rongqian Yang; Shanxing Ou; Dong Xing; Defeng Wang

doi:10.1371/journal.pone.0130730

Nonrigid Registration Regularized by Shape Information: Application to Atlas Construction of Cardiac CT Images

PLoS One. 2015 Jun 25;10(6):e0130730. doi: 10.1371/journal.pone.0130730. eCollection 2015.

Authors

Yunfei Zha¹, Xuesong Lu², Li Wang³, Rongqian Yang⁴, Shanxing Ou⁵, Dong Xing¹, Defeng Wang⁶

Affiliations

¹ Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, P. R. China.
² College of Biomedical Engineering, South-Central University for Nationalities, Wuhan 430074, P. R. China.
³ Department of Infection Control, Renmin Hospital of Wuhan University, Wuhan 430060, P. R. China.
⁴ School of Materials Science and Engineering, South China University of Technology, Guangzhou 510006, P. R. China.
⁵ Radiology Department, Guangzhou General Hospital of Guangzhou Military Area Command, Guangzhou 510010, P. R. China.
⁶ Research Center for Medical Image Computing, Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.

Abstract

Cardiac atlases play an important role in the computer-aided diagnosis of cardiovascular diseases, in particular they need to deal with large and highly variable image datasets. In this paper, we propose a new nonrigid registration algorithm incorporating shape information, to produce comprehensive atlases. For one thing, the multiscale gradient orientation features of images are combined to form the construction of multifeature mutual information. Additionally, the shape information of multiple-objects in images is incorporated into the cost function for registration. We demonstrate the merits of the new registration algorithm on the 3D data sets of 15 patients. The experimental results show that the new registration algorithm can outperform the conventional intensity-based registration method. The obtained atlas can represent the cardiac structures more accurately.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Cardiovascular Diseases / diagnostic imaging*
Diagnosis, Computer-Assisted / methods*
Heart / diagnostic imaging*
Humans
Imaging, Three-Dimensional / methods*
Pattern Recognition, Automated / methods*
Radiography

Grants and funding

This work is supported by the National Natural Science Foundation of China (NSFC) funding (No. 61002046), and partially by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (No. CUHK 416712), a grant from the Innovation and Technology Commission of the Hong Kong Special Administrative Region, China (No. ITS/149/14FP), and a grant from The Science, Technology and Innovation Commission of Shenzhen Municipality (No. CXZZ20140606164105361). The authors would also like to thank Guangzhou General Hospital of Guangzhou Military Area Command for providing the images.