文章基本信息

标题：A novel CAD system to automatically detect cancerous lung nodules using wavelet transform and SVM
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作者：Ayman A. Abu Baker ; Yazeed Ghadi
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2020
卷号：10
期号：5
页码：4745-4751
DOI：10.11591/ijece.v10i5.pp4745-4751
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：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.
关键词：Cancer detection;Computed tomography;DICOM;Wavelet features;Wavelet transform