Computer-aided detection of lung cancer on chest radiographs: algorithm performance vs. radiologists' performance by size of cancer

2001 ◽  
Author(s):  
Matthew T. Freedman ◽  
Shih-Chung B. Lo ◽  
Fleming Y. M. Lure ◽  
Xin-Wei Xu ◽  
Jesse Lin ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Chest Radiographs ◽  
Computer Aided Detection ◽  
Algorithm Performance ◽  
Computer Aided

scholarly journals Computer-aided Detection of Lung Cancer on Chest Radiographs: Effect on Observer Performance

Radiology ◽  
2010 ◽  
Vol 257 (2) ◽  
pp. 532-540 ◽  
Author(s):  
Bartjan de Hoop ◽  
Diederik W. De Boo ◽  
Hester A. Gietema ◽  
Frans van Hoorn ◽  
Banafsche Mearadji ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Chest Radiographs ◽  
Observer Performance ◽  
Computer Aided Detection ◽  
Computer Aided

Computer-aided detection of lung cancer on chest radiographs: effect of machine CAD false-positive locations on radiologists' behavior

2002 ◽  
Author(s):  
Matthew T. Freedman ◽  
Shih-Chung B. Lo ◽  
Teresa Osicka ◽  
Fleming Y. M. Lure ◽  
Xin-Wei Xu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
False Positive ◽  
Chest Radiographs ◽  
Computer Aided Detection ◽  
Computer Aided

Optimal matrix size of chest radiographs for computer-aided detection on lung nodule or mass with deep learning

2020 ◽  
Vol 30 (9) ◽  
pp. 4943-4951
Author(s):  
Young-Gon Kim ◽  
Sang Min Lee ◽  
Kyung Hee Lee ◽  
Ryoungwoo Jang ◽  
Joon Beom Seo ◽  
...  
Keyword(s):  
Deep Learning ◽  
Lung Nodule ◽  
Chest Radiographs ◽  
Computer Aided Detection ◽  
Matrix Size ◽  
Computer Aided

scholarly journals Sensitivity of Computer-Aided Detection (CAD) Device for Lung Nodule Detection on Chest Radiography: A Real-Life Application

2020 ◽  
pp. 1-5
Author(s):  
Ammar Chaudhry ◽  
Ammar Chaudhry ◽  
William H. Moore
Keyword(s):  
Sensitivity And Specificity ◽  
Chest Radiography ◽  
Predictive Value ◽  
Lung Nodule ◽  
Chest Radiographs ◽  
Lung Nodules ◽  
Computer Aided Detection ◽  
Cad System ◽  
Computer Aided ◽  
The Mean

Purpose: The radiographic diagnosis of lung nodules is associated with low sensitivity and specificity. Computer-aided detection (CAD) system has been shown to have higher accuracy in the detection of lung nodules. The purpose of this study is to assess the effect on sensitivity and specificity when a CAD system is used to review chest radiographs in real-time setting. Methods: Sixty-three patients, including 24 controls, who had chest radiographs and CT within three months were included in this study. Three radiologists were presented chest radiographs without CAD and were asked to mark all lung nodules. Then the radiologists were allowed to see the CAD region-of-interest (ROI) marks and were asked to agree or disagree with the marks. All marks were correlated with CT studies. Results: The mean sensitivity of the three radiologists without CAD was 16.1%, which showed a statistically significant improvement to 22.5% with CAD. The mean specificity of the three radiologists was 52.5% without CAD and decreased to 48.1% with CAD. There was no significant change in the positive predictive value or negative predictive value. Conclusion: The addition of a CAD system to chest radiography interpretation statistically improves the detection of lung nodules without affecting its specificity. Thus suggesting CAD would improve overall detection of lung nodules.

Is the Computer-Aided Detection Scheme for Lung Nodule Also Useful in Detecting Lung Cancer?

2008 ◽  
Vol 32 (4) ◽  
pp. 570-575 ◽  
Author(s):  
Jin Mo Goo ◽  
Hyae Young Kim ◽  
Jeong Won Lee ◽  
Hyun Ju Lee ◽  
Chang Hyun Lee ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Nodule ◽  
Computer Aided Detection ◽  
Detection Scheme ◽  
Computer Aided
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