Mono-modal Medical Image Registration with Coral Reef Optimization

Image registration (IR) involves the transformation of different sets of image data having a shared content into a common coordinate system. To achieve this goal, the search for the optimal correspondence is usually treated as an optimization problem. The limitations of traditional IR methods have boomed the application of metaheuristic-based approaches to solve the problem while improving the performance. In this contribution, we consider a recent bio-inspired method: the Coral Reef Optimization Algorithm (CRO). This novel algorithm simulates the natural phenomena underlying a coral reef. We adapt the algorithm following two different approaches: feature-based and intensity-based designs and perform a thorough experimental study in a medical IR problem considering similarity transformations. The results show that CRO overcome the state-of-the-art results in terms of robustness, accuracy, and efficiency considering both approaches.