Computational methods for pigmented skin lesion classification in images: review and future trends

• Type: Another Publication in an International Scientific Journal
• Date: 2018-02

Authors

Roberta B. Oliveira (Author) Other; João P. Papa (Author) Other; Aledir S. Pereira (Author) Other; João Manuel R. S. Tavares (Author) FEUP

Journal

Title: Neural Computing and Applications

Vol. 29 No. 3

Pages: 613-636

ISSN: 0941-0643

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 33 Citations

ISI Web of Science

Scopus - 84 Citations

INSPEC

Scientific classification

FOS: Medical and Health sciences

CORDIS: Technological sciences

Other information

Authenticus ID: P-00K-P3B

DOI: 10.1007/s00521-016-2482-6

Abstract (EN): Skin cancer is considered as one of the most common types of cancer in several countries, and its incidence rate has increased in recent years. Melanoma cases have caused an increasing number of deaths worldwide, since this type of skin cancer is the most aggressive compared to other types. Computational methods have been developed to assist dermatologists in early diagnosis of skin cancer. An overview of the main and current computational methods that have been proposed for pattern analysis and pigmented skin lesion classification is addressed in this review. In addition, a discussion about the application of such methods, as well as future trends, is also provided. Several methods for feature extraction from both macroscopic and dermoscopic images and models for feature selection are introduced and discussed. Furthermore, classification algorithms and evaluation procedures are described, and performance results for lesion classification and pattern analysis are given.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 24