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A novel CAD system to automatically detect cancerous lung nodules using wavelet transform and SVM

Abu Baker, Ayman A.Ghadi, Yazeed
International Journal of Electrical and Computer Engineering (IJECE) (Sinta 1)Vol. 0 No. 01 Oktober 2020
DOI10.11591/ijece.v10i5.pp4745-4751

Abstrak

A novel cancerous nodules detection algorithm for computed tomography images (CT-images) is presented in this paper. CT-images are large size images with high resolution. In some cases, number of cancerous lung nodule lesions may missed by the radiologist due to fatigue. A CAD system that is proposed in this paper can help the radiologist in detecting cancerous nodules in CT- images. The proposed algorithm is divided to four stages. In the first stage, an enhancement algorithm is implement to highlight the suspicious regions. Then in the second stage, the region of interest will be detected. The adaptive SVM and wavelet transform techniques are used to reduce the detected false positive regions. This algorithm is evaluated using 60 cases (normal and cancerous cases), and it shows a high sensitivity in detecting the cancerous lung nodules with TP ration 94.5% and with FP ratio 7 cluster/image.

Kata Kunci

Cancer detectionComputed tomographyDICOMWavelet featuresWavelet transform

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A novel CAD system to automatically detect cancerous lung nodules using wavelet transform and SVM | International Journal of Electrical and Computer Engineering (IJECE) | Publiora