Automated malignant melanoma detection using MATLAB

  • Authors:

  • G. Grammatikopoulos;A. Hatzigaidas;A. Papastergiou;P. Lazaridis;Z. Zaharis;D. Kampitaki;G. Tryfon

  • Affiliations:

  • Department of Esthetics, Alexander Technological Educational Institute of Thessaloniki, EPEAEK II, Thessaloniki, Macedonia, Greece;Department of Electronics, Alexander Technological Educational Institute of Thessaloniki, EPEAEK II, Thessaloniki, Macedonia, Greece;Department of Electronics, Alexander Technological Educational Institute of Thessaloniki, EPEAEK II, Thessaloniki, Macedonia, Greece;Department of Electronics, Alexander Technological Educational Institute of Thessaloniki, EPEAEK II, Thessaloniki, Macedonia, Greece;Department of Electronics, Alexander Technological Educational Institute of Thessaloniki, EPEAEK II, Thessaloniki, Macedonia, Greece;Department of Electronics, Alexander Technological Educational Institute of Thessaloniki, EPEAEK II, Thessaloniki, Macedonia, Greece;Department of Electronics, Alexander Technological Educational Institute of Thessaloniki, EPEAEK II, Thessaloniki, Macedonia, Greece

  • Venue:
  • DNCOCO'06 Proceedings of the 5th WSEAS international conference on Data networks, communications and computers
  • Year:
  • 2006

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Abstract

Malignant melanoma, the most deadly form of skin cancer, has a good prognosis if treated in the curable early stages. Early diagnosis and surgical excision is the most effective treatment of melanoma. Well-trained dermatologists reach a high level of diagnostic accuracy but their performance is increased by using computer aided numerical imaging tools. This study is limited in the use of simple image processing algorithms, for the sake of clarity, in order to illustrate the use of MATLAB in the calculation of the ABCD Total Dermatoscopy Score (TDS) for potentially malignant melanomas. A high ABCD score means that a lesion is more likely to be a malignant melanoma.