Performance of Ensemble Learning Classifiers on Malignant-Benign Classification of Pulmonary Nodules

被引：0

作者：

Tartar, Ahmet ^{[1
]}

Akan, Aydin ^{[2
]}

机构：

[1] Istanbul Univ, Muhendislik Bilimleri Bolumu, TR-34320 Istanbul, Turkey

[2] Istanbul Univ, Elekt Elekt Muhendisligi Bolumu, TR-34320 Istanbul, Turkey

来源：

2014 22ND SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2014年

关键词：

computer-aided diagnosis system; pulmonary nodules; malignant-benign classification; ensemble learning classifiers;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Computer-aided detection systems can help radiologists to detect pulmonary nodules at an early stage. In this study, a novel Computer-aided Diagnosis system (CAD) is proposed for the classification of pulmonary nodules as malignant and benign. Proposed CAD system, providing an important support to radiologists at the diagnosis process of the disease, achieves high classification performance using ensemble learning classifiers.

引用

页码：722 / 725

页数：4

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