Name
Abstract | ||
|---|---|---|
There is a considerable interest in the development of automatic image analysis systems for dermoscopic images. The standard approach usually consists of three stages: (i) image segmentation, (ii) feature extraction and selection, and (iii) lesion classification. This paper evaluates the potential of an alternative approach, based on the Menzies method. It consists on the identification of the presence of 1 or more of 6 possible color classes, indicating that the lesion should be considered a potential melanoma. The Jeffries-Matusita (JM) and Transformed Divergence (TD) separability measures were used for an experimental evaluation with 28 dermoscopic images. In the most challenging case tested, with training identified in multiple images, 8 out of 15 class pairs were found to be well separable, or 13+ 2 out of 21 considering the skin as an additional class. |
Year | Venue | DocType |
|---|---|---|
2012 | COMPUTATIONAL MODELLING OF OBJECTS REPRESENTED IN IMAGES: FUNDAMENTALS, METHODS AND APPLICATIONS III | Conference |
Citations | PageRank | References |
3 | 0.44 | 3 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| André R. S. Marçal | 1 | 137 | 14.47 |
| Teresa Mendonça | 2 | 98 | 19.85 |
| Cátia S. P. Silva | 3 | 6 | 1.16 |
| Marta A. Pereira | 4 | 3 | 0.78 |
| Jorge Rozeira | 5 | 132 | 7.44 |