Beyond Visual Image: Automated Diagnosis of Pigmented Skin Lesions Combining Clinical Image Features with Patient Data

Among the most common types of skin cancer are basal cell carcinoma, squamous cell carcinoma and melanoma. According to the who (2018), currently, between 2 and 3 million non-melanoma skin cancers and 132.000 melanoma skin cancer occur every year in the world. Melanoma is by far the most dangerous form of skin cancer, causing more than 75% of all skin cancer deaths (Allen, 2016). Early diagnosis of the disease plays an important role in reducing the mortality rate with a chance of cure greater than 90% (SBD, 2018). The diagnosis of pigmented skin lesions (PSLs) can be made by invasive and non-invasive methods. One of the most common non-invasive methods was presented by Soyer et al. (1987). The method allows the visualization of morphological structures not visible to the naked eye with the use of an instrument called dermatoscope. When compared to the clinical diagnosis, the use of dermatoscope by experts makes the diagnosis of PSLs easier, increasing by 10-27% the diagnostic sensitivity (Mayer et al., 1997).