Zernike Moment and Mutual Information Based Methods for Multimodal Image Registration

被引:1
|
作者
Kashyap, Suraj Kumar [1 ]
Jat, Dinesh [1 ]
Bhuyan, M. K. [1 ]
Vishwakarma, Amit [1 ]
Gadde, Prathik [2 ]
机构
[1] Indian Inst Technol Guwahati, Dept Elect & Elect Engn, Gauhati 781039, Assam, India
[2] Indiana Univ Purdue Univ, Sch Informat & Comp, 535 West Michigan St, Indianapolis, IN 46202 USA
关键词
Multimodal; Multichannel; MRI; SPECT; Medical image registration; Zernike moment; Enhanced mutual information; Principal component analysis; Canny edge detector; Gradient information; Edge overlap; MAXIMIZATION; GRADIENT;
D O I
10.1007/978-981-32-9291-8_9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Image registration enables joint operations between images obtained from diverse sources. However, there have been limited advances in the registration of multichannel images. The accuracy of registration is a significant concern for medical applications, among others. Two methods, PCA-ZM and CED-ZM, have been proposed for registration based on Zernike moment and enhanced mutual information. Edge detection by Zernike moment and identification of common features in multichannel images are used as a foundation to improve accuracy over single-channel registrations. Single-channel registration accuracy for MRI and SPECT brain images is found to surpass the methods compared against. PCA-ZM demonstrates good accuracy for MR-MR registration, while CED-ZM has good accuracy for MR-SPECT registration. These measures improve upon accurate registration for images, especially where many modalities are available, such as in medical diagnosis.
引用
收藏
页码:100 / 113
页数:14
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