Evaluation of the Menzies method potential for automatic dermoscopic image analysis

• Type: Article in International Conference Proceedings Book
• Date: 2012

Authors

Andre R S Marcal (Author) FCUP; Teresa Mendonca (Author) FCUP; Catia S P Silva (Author) Other; Marta A Pereira (Author) Other; Jorge Rozeira (Author) Other

Conference proceedings International

Title: Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III

Pages: 103-108

International Symposium CompIMAGE 2012 Rome, Italy 5-7 September 2012

Rome, Italy, 5-7 September 2012

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-00G-HTD

DOI: 10.1201/b12753-19

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6