Two segmentation methods for the diagnosis of malignant melanoma

Research output: Contribution to journalArticlepeer-review

Abstract

Automatic diagnosis of malignant melanoma highly depends on the segmentation methods used for the suspicious lesion. We suggest the parameter selection method (PSM) and maximum area method (MAM) for the segmentation of the lesion to be diagnosed. Herein, these segmentation methods are compared to a skin cancer expert’s segmentation and three other conventional algorithms. The diagnoses of malignant melanoma based on the two suggested, three conventional, and expert’s segmentation are compared with respect to sensitivity, specificity, and accuracy.

Original languageEnglish
Pages (from-to)3361-3376
Number of pages16
JournalJournal of Mathematical and Computational Science
Volume11
Issue number3
DOIs
StatePublished - 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • ABCD criteria
  • Image segmentation
  • Maliganant melanoma

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