Joanna Jaworek-Korjakowska, Ryszard Tadeusiewicz
Skin lesion, melanoma, medical image processing, imagemeasurement, diagnosis support
Skin cancer is the most commonly diagnosed type of cancer in all people, regardless of age, gender, or race. One of the most common malignant skin cancer is melanoma which is a dangerous proliferation of melanocytes. In the last several years an increasing melanoma incidence has been observed worldwide, and thediagnosis and deaths are increasing faster than those of any other skin cancer. Only in UK around 12,800 new cases of malignant melanoma were diagnosed in 2010. This paper presents a new approach to the assessment of asymmetry of the pigmented skin lesion. Asymmetry is one of the most important indicator andit contributes substantially to the diagnosis of melanoma in the commonly used diagnostic algorithm, ABCD rule.This paper describes a complex algorithm containing following steps: image enhancement, border detection, lesion segmentation,positioning of axes, and calculation of the asymmetry parameters. The automated asymmetry assessment is based on definition and calculationof the geometry parameters and colour variation (pigmentation, texture) of the lesion. The algorithm has been tested on a database of 100 images (30 malignant lesions and 70 benign lesions). The effectiveness of the proposed method is shown through experiments and compared to diagnosis results by clinical experts. The sensitivity and accuracy have improved significantly.
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