Meta-heuristics play a crucial role in problem optimization, and many are inspired by the collective intelligence observed in natural phenomena. More than 10 percent of women will have breast cancer in their lifetime in the whole globe. Breast MRI registration involves aligning before and after-contrast photos to study and classify cancer categories. This research involves the registration of breast MRI utilizing an enhanced generation of the slime mold algorithm. A meta-heuristic method is proposed, AOSMA is a meta-heuristic optimization technique that assesses the registration of MRI of breasts. After that, the AOSMA algorithm prosperously registered the images. The outcome of the AOSMA-based registration approach is contrasted with registration based on the GTO and PSO methods. The outcome implicates, an example of registration of breast MR images, a technique that is based upon the AOSMA algorithm that trumps the GTO-based and PSO-based registration methods.