Bacterial Foraging Optimization for intensity-based medical image registration

Abstract

Image registration (IR) or image alignment is a fundamental step in medical image analysis when multiple images are involved. In most of such applications, the registration is performed following the intensity-based approach, which turns IR into a complex, computationally expensive, continuous optimization problem. In this paper, we introduce a new technique for intensity-based medical IR using the Bacterial Foraging Optimization Algorithm (BFOA), a novel bio-inspired metaheuristic. BFOA has recently obtained promising results in many real-world applications, including feature-based IR. The new algorithm is compared on a complex medical IR application against recent, outstanding IR techniques both traditional and based on meta-heuristics. The results show that our proposal is competitive with the state of the art, making BFOA a promising solution to tackle other complex, real-world optimization problems.