A Novel Model for Smart Breast Cancer Detection in Thermogram Images

被引：2
|
作者：
Kazerouni, Iman Abaspur [1 ]
Zadeh, Hossein Ghayoumi [1 ]
Haddadnia, Javad [1 ]
机构：
[1] Hakim Sabzevari Univ, Dept Elect Engn, Sabzevar, Iran
来源：
ASIAN PACIFIC JOURNAL OF CANCER PREVENTION | 2014年 / 15卷 / 24期
关键词：
Thermographic image; hot area; support vector machine; feature extraction;
D O I：
10.7314/APJCP.2014.15.24.10573
中图分类号：
R73 [肿瘤学];
学科分类号：
100214 ;
摘要：
Background: Accuracy in feature extraction is an important factor in image classification and retrieval. In this paper, a breast tissue density classification and image retrieval model is introduced for breast cancer detection based on thermographic images. The new method of thermographic image analysis for automated detection of high tumor risk areas, based on two-directional two-dimensional principal component analysis technique for feature extraction, and a support vector machine for thermographic image retrievalwas tested on 400 images. The sensitivity and specificity of the model are 100% and 98%, respectively.
引用
收藏
页码：10573 / 10576
页数：4
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