Paper Info
Title
Computational methods for pigmented skin lesion classification in images: review and future trends.
Abstract
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.
Year
DOI
Venue
2018
10.1007/s00521-016-2482-6
Neural Computing and Applications
Keywords
Field
DocType
Pattern analysis, Feature extraction and selection, Classification methods, Macroscopic and dermoscopic images
Feature selection,Lesion,Skin cancer,Feature extraction,Artificial intelligence,Radiology,Melanoma,Statistical classification,Machine learning,Cancer,Mathematics,PIGMENTED SKIN LESION
Journal
Volume
Issue
ISSN
29
3
1433-3058
Citations 
PageRank 
References 
15
0.60
83
Authors
4
Name
Order
Citations
PageRank
Roberta B. Oliveira1482.31
João P. Papa268946.87
Aledir Silveira Pereira3786.72
João Manuel R. S. Tavares460362.85