A New Method for Segmentation of Skin Lesions in Dermoscopy Images: Energy Optimization Based on the Radial Directions

Detecting lesion borders is the first step for intelligent lesion identification in dermoscopy, therefore it may influence the accuracy and validity of the next steps of this process. Unfortunately, extracting borders is hampered by some challenges such as losses associated with irregular borders, poor contrast, and artifacts encountered in some area. In this paper, the improved version of energy function optimization technique is introduced in order to separate the skin and lesions in the processing of dermoscopy images. This technique is based on the concept of radial directions in the contour development process, which reduces the sensitivity of estimating the boundaries of lesions to the above constraints. The performance of the proposed method is evaluated on a dataset of dermoscopy images which are captured from various lesions with different sizes and boundaries. The obtained results of the proposed method are compared with some other state-of-the-art lesion detection methods by using standard parameters. Increased True Detection Rate by 6.17% in parallel with decrease in Hammoud Distance by 2.3%, both compared to the best among alternative methods shows the effectiveness of the proposed scheme in detecting lesion borders of dermoscopy images.