الفهرس 
Feature extraction enhancement for category classification
AbstractOnly 14 pages are availabe for public view
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Abstract
Computer aided diagnosis is starting to be implemented broadly in the diagnosis and detection of many varieties of abnormities acquired during various imaging procedures. The main aim of the CAD systems is to increase the accuracy and decrease the time of diagnoses, while the general achievement for CAD systems are to find the place of nodules and to determine the characteristic features of the nodule. As lung cancer is one of the fatal and leading cancer types, there has been plenty of studies for the usage of the CAD systems to detect lung cancer. Yet, the CAD systems need to be developed a lot in order to identify the different shapes of nodules, lung segmentation and to have higher level of sensitivity, specificity and accuracy. This challenge is the motivation of this study in implementation of CAD system for lung cancer detection. Multiple approaches involving diverse conceptualizations are developed to represent and recognize lung cancer from CT scans