Abstract
Automatic lesion segmentation is an important part of computer-based image analysis of pigmented skin lesions. Currently, there is a great interest in th e development of Computer-Aided Diagnosis (CAD) systems for dermoscopic images. The segmentation step is one of the most important ones, since its accuracy determines the eventual success or failure of a CAD system. This study introduced new method of dermoscopic images segmentation. The preprocess was the filtering operation to dermoscopy image to rem ove most of difficulties facing the efficient segmentat ions, like a variety of lesion shapes, sizes, color , changes due to different skin types and textures and presence o f hairs. Segmentation based mainly on histogram thresholding. The enhancements of image achieved by using mathematical morphology in order to obtain better segmentation with smooth border and without any noise in the lesion region. The proposed method evaluated by using Hammoude Distance (HM) and the True Detection Rate (TDR). Also the proposed method is compared with other skin lesions segmentation methods such as Otsu, adaptive thresholding and fuzzy Cmeans. The accuracy of proposed method was 96.32%, which is highly promised result and dependable.
Highlights
INTRODUCTIONThere are three common steps in dermoscopic image analysis, which are: Malignant melanoma is the most common type of skin cancer; its spread has been growing rapidly over the past few decades
Let denote X to a resulted image from proposed automatic segmentation method and Y denote the segmented image achieved by expert physicians
There are two errors may be counted in this process, the first one is pixels classified as a pest by the medical expert while did not classified as pest by proposed method, where the second error is pixels classified as pest by proposed algorithm and did not classified as pest by a medical expert
Summary
There are three common steps in dermoscopic image analysis, which are: Malignant melanoma is the most common type of skin cancer; its spread has been growing rapidly over the past few decades It is the most treatable type of skin cancer if it is detected at an early stage (Silveira et al, 2009). Algorithms try to isolate the lesion area from the rest of Dermoscopy and telemedicine have been important the image in order to permit an easier observation and developments in the past few years. This will help diagnosis of the lesion. Xie and Bovik (2013) proposed new segmentation method for dermoscopy image based on combining two algorithms, Self Generating Neural Network and the Genetic Algorithm (GA).
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