Computational vision systems for the detection of malignant melanoma

  • Authors:
    • Ilias Maglogiannis
    • Dimitrios I. Kosmopoulos
  • View Affiliations

  • Published online on: April 1, 2006     https://doi.org/10.3892/or.15.4.1027
  • Pages: 1027-1032
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Abstract

In recent years, computational vision-based diagnostic systems for dermatology have demonstrated significant progress. We review these systems by first presenting the installation, visual features utilized for skin lesion classification and the methods for defining them. We also describe how to extract these features through digital image processing methods, i.e. segmentation, registration, border detection, color and texture processing, and present how to use the extracted features for skin lesion classification by employing artificial intelligence methods, i.e. discriminant analysis, neural networks, and support vector machines. Finally, we compare these techniques in discriminating malignant melanoma tumors versus dysplastic naevi lesions.

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Journal Cover

April 2006
Volume 15 Issue 4

Print ISSN: 1021-335X
Online ISSN:1791-2431

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Spandidos Publications style
Maglogiannis I and Kosmopoulos DI: Computational vision systems for the detection of malignant melanoma. Oncol Rep 15: 1027-1032, 2006.
APA
Maglogiannis, I., & Kosmopoulos, D.I. (2006). Computational vision systems for the detection of malignant melanoma. Oncology Reports, 15, 1027-1032. https://doi.org/10.3892/or.15.4.1027
MLA
Maglogiannis, I., Kosmopoulos, D. I."Computational vision systems for the detection of malignant melanoma". Oncology Reports 15.4 (2006): 1027-1032.
Chicago
Maglogiannis, I., Kosmopoulos, D. I."Computational vision systems for the detection of malignant melanoma". Oncology Reports 15, no. 4 (2006): 1027-1032. https://doi.org/10.3892/or.15.4.1027