Automatically Early Detection of Skin Cancer: Study Based on Nueral Netwok Classification

被引:29
作者
Lau, Ho Tak [1 ]
Al-Jumaily, Adel [1 ]
机构
[1] Univ Technol Sydney, Fac Engn, Sch Elect Mech & Mechatron Syst, Sydney, NSW 2007, Australia
来源
2009 INTERNATIONAL CONFERENCE OF SOFT COMPUTING AND PATTERN RECOGNITION | 2009年
关键词
Skin cancer; classification; neural network; computer based detaction;
D O I
10.1109/SoCPaR.2009.80
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, an automatically skin cancer classification system is developed and the relationship of skin cancer image across different type of neural network are studied with different types of preprocessing.. The collected images are feed into the system, and across different image processing procedure to enhance the image properties. Then the normal skin is removed from the skin affected area and the cancer cell is left in the image. Useful information can be extracted from these images and pass to the classification system for training and testing. Recognition accuracy of the 3-layers back-propagation neural network classifier is 89.9% and auto-associative neural network is 80.8% in the image database that include dermoscopy photo and digital photo
引用
收藏
页码:375 / 380
页数:6
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