Abstract
A Computer Aided Diagnosis (CAD) system has a significant importance and key role in cancer detection especially from lungs by using medical imaging modalities. It is much helpful to the radiologists by providing a second opinion regarding diagnosis which improves their performance in terms of time and precision. This work examines the effectiveness of automatic cancer detection methods from lungs using Computed Tomography (CT) images and provides a detailed survey of different techniques, algorithms which are used in nodule detection in recent years. We intend to give the readers a comprehensive view of existing research and a range of feature extraction, classification, and segmentation algorithms. We have also assessed some performance measures used to evaluate the correctness of a CAD system including sensitivity; specificity, accuracy, and false positive rate. This review will give a detailed picture and provides insight into the current developments in the field of Computer Aided Diagnosis.
Keywords: Computer Aided Diagnosis (CAD), Computed Tomography (CT), Lung nodule, Medical imaging, Segmentation, Classification.
Graphical Abstract
Call for Papers in Thematic Issues
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