Application of Image Registration Techniques to Medical CT and MR Images.
Moustafa, H., Rehan, S. (2020). Application of Image Registration Techniques to Medical CT and MR Images.. EKB Journal Management System, 32(2), 49-57. doi: 10.21608/bfemu.2020.128296
Hossam El_Din Moustafa; Sameh Rehan. "Application of Image Registration Techniques to Medical CT and MR Images.". EKB Journal Management System, 32, 2, 2020, 49-57. doi: 10.21608/bfemu.2020.128296
Moustafa, H., Rehan, S. (2020). 'Application of Image Registration Techniques to Medical CT and MR Images.', EKB Journal Management System, 32(2), pp. 49-57. doi: 10.21608/bfemu.2020.128296
Moustafa, H., Rehan, S. Application of Image Registration Techniques to Medical CT and MR Images.. EKB Journal Management System, 2020; 32(2): 49-57. doi: 10.21608/bfemu.2020.128296

Application of Image Registration Techniques to Medical CT and MR Images.

MEJ- Mansoura Engineering Journal
Article 10, Volume 32, Issue 2, June 2007, Page 49-57  XML PDF (544.38 K)
Document Type: Research Studies
DOI: 10.21608/bfemu.2020.128296
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Authors
Hossam El_Din Moustafa* 1; Sameh Rehan2
1Communications and Electronics Engineering Department Faculty of Engineering, Mansoura University Mansoura, EGYPT 35516
2(Senior IEEE member) Communications and Electronics Engineering Department Faculty of Engineering, Mansoura University Mansoura, Egypt 35516
Abstract
Image registration has become one of the most widely used techniques in computer vision. Its applications include optical flow, notion analysis, tracking, face detection, and biomedical image registration. In the present work, three different techniques of image registration were implemented and applied to both Computed Tomography (CT) and Magnetic Resonance (MR) images. The first technique is based on Cross Correlation (CC). The second approach depends on Control Points' Selection (CPS) from both the reference and the input images. The last technique is based on Maximization of Mutual Information (MMI) between We two images. The registrability is calculated for each image to measure its ability to provide unambiguous registration, by providing clear correlation peaks when registered with other subimage. Then, the three registration techniques were evaluated and compared using both the Weighted Peak Signal to Noise Ratio (WPSNR) and the Normalized Cross Correlation Coefficient (NCCC). The application of the selected techniques to CT and MR images has shown that registration based on MMI has given the best results and can be used efficiently for alignment of CT and MR images. 
Keywords
image registration; mutual information; weighted peak signal to noise ratio; CT images; MR images; registrability
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