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 language | English |
|---|---|
| Pages (from-to) | 3361-3376 |
| Number of pages | 16 |
| Journal | Journal of Mathematical and Computational Science |
| Volume | 11 |
| Issue number | 3 |
| DOIs | |
| State | Published - 2021 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- ABCD criteria
- Image segmentation
- Maliganant melanoma
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