Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: Localized search method based on anatomical classification

2006 ◽  
Vol 33 (7Part1) ◽  
pp. 2642-2653 ◽  
Author(s):  
Junji Shiraishi ◽  
Qiang Li ◽  
Kenji Suzuki ◽  
Roger Engelmann ◽  
Kunio Doi
Keyword(s):  
Search Method ◽  
Chest Radiographs ◽  
Lung Nodules ◽  
Anatomical Classification ◽  
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.

Computer-aided detection (CAD) of lung nodules and small tumours on chest radiographs

2009 ◽  
Vol 72 (2) ◽  
pp. 218-225 ◽  
Author(s):  
D.W. De Boo ◽  
M. Prokop ◽  
M. Uffmann ◽  
B. van Ginneken ◽  
C.M. Schaefer-Prokop
Keyword(s):  
Chest Radiographs ◽  
Lung Nodules ◽  
Computer Aided Detection ◽  
Computer Aided

scholarly journals New methods for using computer-aided detection information for the detection of lung nodules on chest radiographs

2014 ◽  
Vol 87 (1036) ◽  
pp. 20140015 ◽  
Author(s):  
S Schalekamp ◽  
B van Ginneken ◽  
BGF Heggelman ◽  
M Imhof-Tas ◽  
I Somers ◽  
...  
Keyword(s):  
Chest Radiographs ◽  
Lung Nodules ◽  
Computer Aided Detection ◽  
New Methods ◽  
Computer Aided

Improved Detection of Lung Nodules on Chest Radiographs Using a Commercial Computer-Aided Diagnosis System

2004 ◽  
Vol 182 (2) ◽  
pp. 505-510 ◽  
Author(s):  
Shingo Kakeda ◽  
Junji Moriya ◽  
Hiromi Sato ◽  
Takatoshi Aoki ◽  
Hideyuki Watanabe ◽  
...  
Keyword(s):  
Computer Aided Diagnosis ◽  
Chest Radiographs ◽  
Lung Nodules ◽  
Diagnosis System ◽  
Computer Aided ◽  
Aided Diagnosis

scholarly journals Computer-Aided Detection of Malignant Lung Nodules on Chest Radiographs: Effect on Observers' Performance

2012 ◽  
Vol 13 (5) ◽  
pp. 564 ◽  
Author(s):  
Kyung Hee Lee ◽  
Jin Mo Goo ◽  
Chang Min Park ◽  
Hyun Ju Lee ◽  
Kwang Nam Jin
Keyword(s):  
Chest Radiographs ◽  
Lung Nodules ◽  
Computer Aided Detection ◽  
Computer Aided
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