This paper introduces a novel algorithm for the automatic segmentation of image datasets. The proposed methodology integrates various techniques for preprocessing, segmentation, and quality enhancement, including morphological operators. The algorithm is designed to optimize the segmentation. it uses a Differential Evolution (DE) algorithm to find the best combination of techniques for a specific dataset, guided by a set of Ground Truth images. Experimental results demonstrate that the proposed method significantly outperforms current state-of-the-art techniques, achieving a substantial improvement in segmentation accuracy and quality.