1. Introduction

Melanoma, also known as malignant melanoma, is the most dangerous type of skin cancer that progresses from the pigment-containing cells known as melanocytes. Sometimes they progress from a mole with concerning changes including an increase in size, irregular edges, and change in color, itchiness, or skin breakdown [1]. Melanomas may rarely occur in the mouth, intestines, or eye but typically occur in the skin [1, 2]. In men, they most commonly occur on the back, while in women, they are most common on the legs [2].

Authors of [2] also mentioned that the ultraviolet light (UV) exposure from either the sun or from other sources, such as tanning devices is the primary cause of melanoma, while about 25% develop from moles. Worldwide, in 2012, it registered 55,000 death cases in 232,000 people. North America, Europe, Australia, and New

Zealand have the highest rates of melanoma in the world while it is less common in Latin America, Asia, and Africa.

One of the widely used methods by dermatologists to classify the cancerous skin —melanoma from normal skin is the ABCD rule. It is proved that it can be easily learned and rapidly calculated and has been proven to be a reliable method providing a more objective and reproducible diagnosis of melanoma [3–5]. To calculate the ABCD score, the "asymmetry, border, colors, and diameter" criteria are approximately estimated (semi-quantitatively). Each of the criteria is then multiplied by a given weight factor to yield a total dermoscopy score (TDS). TDS values less than 4.75 indicate a benign melanocytic lesion, values between 4.8 and 5.45 indicate a suspicious lesion, and values of 5.45 or greater are highly suggestive of melanoma.

To calculate the Asymmetry, the melanocytic lesion is bisected by two 90° axes. If both axes dermoscopically show asymmetric contours with regard to shape, the asymmetry score is 2. If there is asymmetry on one axis only, the score is 1. If asymmetry is absent with regard to both axes the score is 0. The border is calculated by dividing the lesion into eighths. Within each one-eighth, a sharp, abrupt cut-off of pigment pattern at the periphery receives a score 1, otherwise receives a score 0. Color feature is calculated by counting the existence of six different colors: white, red, light brown, dark brown, blue-gray, and black. The Diameter of melanomas is usually greater than 6 mm.

The proposed work relies on extracting and selecting specific information features that can be used to distinguish malignant, suspicious, and benign lesions by setting an automated cancer diagnosis using image processing techniques. More details on the image processing techniques used in this research exist in [6].

To achieve the aim of this research, four stages are implemented sequentially:


Section 2 describes an overview of several systems proposed in the literature. Section 3 describes the research methodology. The experimental study and discussion are described in Section 4. Section 5 concludes this paper with some remarks on future work.

Diagnosis of Skin Lesions Based on Dermoscopic Images Using Image Processing Techniques DOI: http://dx.doi.org/10.5772/intechopen.88065
