Abstract
In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in cancerous skin spots. Finally a spectral index is calculated to obtain a range of spectral indices defined for skin cancer. Our results show a confidence level of 95.4%.
Highlights
Skin cancer is one of the diseases that affect humans
Squamous cell carcinoma is the second most common type of skin cancer, which appears in the cells that make up the upper skin layers, it is more likely to spread to areas under the skin
The images were classified as basal cell carcinoma, squamous cell carcinoma and melanoma by certified dermatologists after histopathological examination
Summary
Skin cancer is one of the diseases that affect humans. It is caused by the development of cancerous cells on any of the layers of skin and occurs when cells in a body part begin to grow out of control and spread to other organs and tissues. The spectral technique is based on the Fourier analysis of the image to obtain the spatial period of texture in this way a “regions with network” mask is created This mask joins with segmented mask obtaining a “network image”, where the lesion area and pigment network are highlight. The majority of the studies published in the literature such as [16,17,18] include similar stages as in the works mentioned above These methods consists, generally of four stages which are: (i) acquire de image set, (ii) segmentation (which include several methods i.e techniques based on edges, thresholding, histogram segmentation, region growing, etc.), (iii) feature extraction (iv) classification or detection of a lesion for diagnosis. Fourier spectral analysis techniques have demonstrated the capability to analyze important features from images in several fields being one of the most powerful tools
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