Computer-aided diagnosis in chest radiography: results of large-scale observer tests at the 1996-2001 RSNA scientific assemblies.
Since 1996, computer-aided diagnosis (CAD) schemes have been presented as interactive demonstrations on computer workstations at each scientific assembly of the Radiological Society of North America. The schemes involved (a) detection of pulmonary nodules, (b) temporal subtraction, (c) detection of interstitial lung disease, (d) differential diagnosis of interstitial lung disease, and (e) distinction between benign and malignant pulmonary nodules on chest radiographs. Large-scale observer tests were carried out to examine how radiologists can benefit from CAD systems. Observer performance was evaluated by analysis of receiver operating characteristic (ROC) curves. The statistical significance of the difference between the areas under the ROC curves without and with CAD was analyzed with the Student t test. In all of the tests, the diagnostic accuracy of the radiologists in total improved significantly when CAD was used. This result provides additional evidence that CAD has the potential to improve the performance of radiologists in their decision-making process in interpreting chest radiographs.
Abe
Hiroyuki
H
Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, MC-2026, University of Chicago, 5841 S Maryland Ave, Chicago, IL 60637, USA. habe@uchicago.edu
MacMahon
Heber
H
Engelmann
Roger
R
Li
Qiang
Q
Shiraishi
Junji
J
Katsuragawa
Shigehiko
S
Aoyama
Masahito
M
Ishida
Takayuki
T
Ashizawa
Kazuto
K
Metz
Charles E
CE
Doi
Kunio
K
D003936:Diagnosis, Computer-Assisted; D003937:Diagnosis, Differential; D006801:Humans; D017563:Lung Diseases, Interstitial / Q000000981:diagnostic imaging; D016571:Neural Networks, Computer; D012372:ROC Curve; D013902:Radiography, Thoracic; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging