Proposed Watershed Technique Based on Whale Optimized Algorithm for Medical Images Segmentation (WAWOA)

Abstract

Image segmentation is a way which applied to split an image for many parts. It will generate image smooth and easy to evaluate. A useful image segmentation technique is help the area authority in medical images. Also, a good segmented images are important in many medical fields like radiologist, pathologist of quick and successful analysis. It has used effectively in diagnosis for many disease. Nature inspired algorithms imitate the mathematical and innovative techniques for non-linear and actuality problems and can be achieved to segment or analyses the images. In this paper, a watershed as segmentation technique (WAWOA) has applied to segment the medical dataset image then proposed a whale based segmentation technique which can be used on medical bones image anyways the nature or style of the image. For fair analysis of these techniques, peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM) and Universal Image Quality Index (UIQI) of segmented images are analyzed by using MATLAB. The success of the proposed technique has confirmed with evaluated via comparing the obtained with outed results beside a standard watershed technique. The results showed this technique develops the segmentation of medical images and can help with better diagnosis. The evaluation results of our proposed technique show the success and efficiency of segmented images in high rates.