الفهرس 
IntroductionOnly 14 pages are availabe for public view
 |  | from | 133 |  |  |
| | | from | 133 | | |
Abstract
Lung cancer is considered the most common cause of cancer-related deaths in developed and developing countries. In 2014, the American College of Radiology (ACR) published the Lung Imaging Reporting and Data System )Lung-RADS( Categories to standardize the CT lung screening reporting and management recommendations and facilitates outcome monitoring (Martin et al., 2017). This study introduces an automated system/software (AVIEW Metric software) developed by Coreline Soft i.e. Coreline soft is a Korean medical image software company. This software can detect and classify lung nodules in lung CT scans. Data were collected retrospectively from the previously mentioned study population through PACS (Picture Achieving and Communication System). A total of 79 CT scans and total of 253 pulmonary nodules were manually reviewed by two radiologists using PACS and then automatically reviewed by the research radiologist using Coreline Soft’s AVIEW Metric software. Then these results were compared to a reference senior radiologist
There was significant difference between radiologist A, B and CAD in detection of pulmonary nodules, with significant improvement of the detection of the pulmonary nodules after using the CAD method. This improvement is seen regardless the size and consistency of the noduleAs for the detection of the pulmonary nodules, the initial review by the CAD system (Unrevised by the research radiologist) has high sensitivity (93.0%) and specificity (95.5 %) with overall accuracy of 93.6 %.
After 2nd look and revision of the automated detected nodules was done, revised final computer aided detection has higher sensitivity (98.2%) and comparable specificity (95.5 %) for the detection of pulmonary nodules with overall accuracy of 97.4 %.