A Computer Aided Diagnosis System for Lung Cancer Detection Using Support Vector Machine | Science Publications

American Journal of Applied Sciences

M. Gomathi¹  P. Thangaraj¹ 

关键词: Computer Aided Diagnosis (CAD);    Support Vector Machine (SVM);    False Positive Rates (FPR);    Fuzzy Possibilistic C Mean (FPCM);    Support Vector Machine (EVM);    Computer Tomography (CT);    Possibility C-Means (PCM);    Fuzzy C-Means (FCM);    Artificial Neural Network (ANN);   

DOI  :  10.3844/ajassp.2010.1532.1538

学科分类：自然科学（综合）

来源: Science Publications

【 摘 要 】

Problem statement: Computer Tomography (CT) has been considered as the most sensitiveimaging technique for early detection of lung cancer. Approach: On the other hand, there is arequirement for automated methodology to make use of large amount of data obtained CT images.Computer Aided Diagnosis (CAD) can be used efficiently for early detection of Lung Cancer. Results:The usage of existing CAD system for early detection of lung cancer with the help of CT images hasbeen unsatisfactory because of its low sensitivity and False Positive Rates (FPR). This study presents aCAD system which can automatically detect the lung cancer nodules with reduction in false positiverates. In this study, different image processing techniques are applied initially in order to obtain thelung region from the CT scan chest images. Then the segmentation is carried with the help of FuzzyPossibility C Mean (FPCM) clustering algorithm. Conclusion/Recommendations: Finally forautomatic detection of cancer nodules, Support Vector Machine (SVM) is used which helps in betterclassification of cancer nodules. The experimentation is conducted for the proposed technique by 1000CT images collected from the reputed hospital.

【 授权许可】

Unknown