3D Inter-subject Medical Image Registration by Scatter Search

• Published in: Hybrid Metaheuristics pp. 90 - 103
• Main Authors: Cordón, Oscar, Damas, Sergio, Santamaría, J., Martí, Rafael
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2005; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Algorithmics. Computability. Computer arithmetics; Applied sciences; Artificial intelligence; Computer science; control theory; systems; Exact sciences and technology; Flows in networks. Combinatorial problems; Image Registration; Iterative Close Point; Mean Square Error; Memetic Algorithm; Operational research and scientific management; Operational research. Management science; Pattern recognition. Digital image processing. Computational geometry; Problem Instance; Theoretical computing; Image registration; Local search; Computer vision; Image processing; Image retrieval; Diversification; Combinatorial optimization; Search algorithm; Image matching; Heuristic method; Medical imagery; Tridimensional image; Medical application
• ISBN: 3540285350; 9783540285359
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/11546245_9

Image registration is a very active research area in computer vision, namely it is used to find a transformation between two images taken under different conditions. Point matching is an image registration approach based on searching for the right pairing of points between the two images. From this matching, the registration transformation we are searching, can be inferred by means of numerical methods. In this paper, we propose a scatter search (SS) algorithm to solve the matching problem. SS is a hybrid metaheuristic with a good trade-off between search space diversification and intensification. On the one hand, diversity is basically introduced from a population-based approach where systematic combinations of subsets of solutions are performed. On the other hand, intensification is achieved with a local search procedure, to ensure the local improvement of promising solutions. Our computational experimentation in a real-world inter-subject medical registration environment establishes the effectiveness of our procedure in relation to different approaches usually applied to solve the problem.