Employing the Local Radon Transform for Melanoma Segmentation in Dermoscopic Images

Alireza Amoabedini, Mahsa Saffari Farsani, Hamidreza Saberkari, Ehsan Aminian

Abstract


In recent years, the number of patients suffering from melanoma, as the deadliest type of skin
cancer, has grown signifcantly in the world. The most common technique to observe and diagnosis
of such cancer is the use of noninvasive dermoscope lens. Since this approach is based on the expert
ocular inference, early stage of melanoma diagnosis is a diffcult task for dermatologist. The main
purpose of this article is to introduce an effcient algorithm to analyze the dermoscopic images. The
proposed algorithm consists of four stages including converting the image color space from the RGB
to CIE, adjusting the color space by applying the combined histogram equalization and the Otsu
thresholding‑based approach, border extraction of the lesion through the local Radon transform, and
recognizing the melanoma and nonmelanoma lesions employing the ABCD rule. Simulation results
in the designed user‑friendly software package environment confrmed that the proposed algorithm
has the higher quantities of accuracy, sensitivity, and approximation correlation in comparison with
the other state‑of‑the‑art methods. These values are obtained 98.81 (98.92), 94.85 (89.51), and
90.99 (86.06) for melanoma (nonmelanoma) lesions, respectively.


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