A Study on Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images

Author:

Al-Mansour Ebtihal Abdullah1,Jaffar M. Arfan1

Affiliation:

1. Al Imam Mohammad Ibn Saud Islamic (IMSIU), Saudi Arabia

Abstract

Malignant Melanoma is one of the rare and the deadliest form of skin cancer if left untreated. Death rate due to this cancer is three times more than all other skin-related malignancies combined. Incidence rates of melanoma have been increasing, especially among young adults, but survival rates are high if detected early. There is a need for an automated system to assess a patient's risk of melanoma using digital dermoscopy, that is, a skin imaging technique widely used for pigmented skin lesion inspection. Although many automated and semi-automated methods are available to diagnose skin cancer but each has its own limitations and there is no final, state-of-the art technique to date which is able to be implemented in real scenario. This survey paper is based on techniques used to segment the skin cancer, analysis of their merits and demerits and their applications on advanced imaging techniques.

Publisher

IGI Global

Reference47 articles.

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2. Lu, C., Mahmood, M., Jha, N., & Mandal, M. (2013). Automated Segmentation of the Melanocytes in Skin Histopathological Images. IEEE Journal of Biomedical and Health Informatics, 17(2).

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4. From Local Patterns to Classification Models

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