T1 and T2 MRI Brain Images Registration and Fusion Technique
Sunanda Dixit1, Mahesh B V2, Suma V3

1Sunanda Dixit, Computer Science and Engineering Department, BMS Institute of Technology and Management, Bangalore, India.
2Mahesh B V. , Tata consultancy Services, Bangalore, India.
3Suma.V, Information Science and Engineering department, Dayananda Sagar College of Engineering, Bangalore, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 20, 2020. | Manuscript published on March 30, 2020. | PP: 1113-1117 | Volume-8 Issue-6, March 2020. | Retrieval Number: E6626018520/2020©BEIESP | DOI: 10.35940/ijrte.E6626.038620

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Fusion of the medical images and registering them will improve the diagnosis and treatment for brain pathology. Image registration plays a major role because multimodal images intensity levels are to be aligned based on relationship between the images. Image registration is proposed where T1 image is a target image where T2 is registering image. Optical flow with SIFT is applied to register T2 image. The registered T2 image is fused with T1 image by applying curvelet transformation and averaging method. Entropy and Mutual Information (MI) parameter is used to evaluate the system performance. The results of the system give better entropy and MI value.
Keywords: Registration, Fusion, MRI, Optical Flow, SIFT, Curvelet transformation, Mutual Information (MI), Entropy.
Scope of the Article: Security Technology and Information Assurance.