Comparison of segmentation methods for automatic diagnosis of dermoscopy images

• Type: Article in International Conference Proceedings Book
• Date: 2007

Authors

Teresa Mendonca (Author) FCUP; Andre R S Marcal (Author) FCUP; Angela Vieira (Author) Other; Jacinto C Nascimento (Author) Other; Margarida Silveira (Author) Other; Jorge S Marques (Author) Other; Jorge Rozeira (Author) Other

Conference proceedings International

Title: PROCEEDINGS OF ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY

Pages: 6573-6576

29th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society

Lyon, FRANCE, AUG 22-26, 2007

Indexing

ISI Web of Knowledge - 17 Citations

Scopus - 20 Citations

Scientific classification

FOS: Engineering and technology > Environmental biotechnology

Other information

Authenticus ID: P-004-EZ4

DOI: 10.1109/iembs.2007.4353865

Abstract (EN): Dermoscopy is a non-invasive diagnostic technique for the in vivo observation of pigmented skin lesions used in dermatology. There is currently a great interest in the prospects of automatic image analysis methods for dermoscopy, both to provide quantitative information about a lesion, which can be of relevance for the clinician, and as a stand alone early warning tool. The effective implementation of such a tool could lead to a reduction in the number of cases selected for exeresis, with obvious benefits both to the patients and to the health care system. The standard approach in automatic dermoscopic image analysis has usually three stages: (i) image segmentation, (ii) feature extraction and feature selection, (iii) lesion classification. This paper presents a comparison of segmentation methods applied to 50 dermoscopic image analysis, along with a clinical evaluation of each segmentation result performed by an experienced dermatologist.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4