title: Multimodality medical image registration and fusion techniques using mutual information and genetic algorithm-based approaches.
abstract: Medical image fusion has been used to derive the useful complimentary information from multimodal images. The prior step of fusion is registration or proper alignment of test images for accurate extraction of detail information. For this purpose, the images to be fused are geometrically aligned using mutual information (MI) as similarity measuring metric followed by genetic algorithm to maximize MI. The proposed fusion strategy incorporating multi-resolution approach extracts more fine details from the test images and improves the quality of composite fused image. The proposed fusion approach is independent of any manual marking or knowledge of fiducial points and starts the procedure automatically. The performance of proposed genetic-based fusion methodology is compared with fuzzy clustering algorithm-based fusion approach, and the experimental results show that genetic-based fusion technique improves the quality of the fused image significantly over the fuzzy approaches.
authors: Indian Institute of Information Technology & Management, Morena Link Road, Gwalior, 474010, India. mb@iiitm.ac.in
authors: Mahua
authors: M
authors: Bhattacharya
authors: Arpita
authors: A
authors: Das
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology / Q000000981:diagnostic imaging; D016000:Cluster Analysis; D019295:Computational Biology; D003952:Diagnostic Imaging / Q000706:statistics & numerical data*; D017143:Fuzzy Logic; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data; D013382:Subtraction Technique / Q000706:statistics & numerical data; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data