Computer-aided diagnosis for improved detection of lung nodules by use of posterior-anterior and lateral chest radiographs.
OBJECTIVE
We developed a computerized scheme for detection of lung nodules in the lateral views of chest radiographs, in order to improve the overall performance in combination with the computer-aided diagnostic (CAD) scheme for posterior-anterior (PA) views.


METHODS
We used 106 pairs of PA and lateral views of chest radiographs (122 lung nodules) for development of the CAD scheme. In the CAD scheme for lateral views, initial candidates of lung nodules were identified by use of a nodule enhancement filter based on the edge gradients. Thirty-four image features extracted from the original and the nodule-enhanced images were used for the rule-based scheme and for artificial neural networks (ANNs) for removal of some false-positive candidates. The computer performance was evaluated with a leave-one-case-out test method for ANNs. For PA views, we used the existing CAD scheme, which was trained with one-half of 924 chest images and then tested with the remaining images.


RESULTS
When the CAD scheme was applied only to PA views, the sensitivity in the detection of lung nodules was 70.5%, with 4.9 false positives per image. Although the performance of the computerized scheme for lateral views was relatively low (60.7% sensitivity with 1.7 false positives per image), the overall sensitivity (86.9%) was improved (6.6 false positives per two views), because 20 (16.4%) of the 122 nodules were detected only on lateral views.


CONCLUSIONS
The CAD scheme by use of lateral-view images has the potential to improve the overall performance for detection of lung nodules on chest radiographs when combined with a conventional CAD scheme for standard PA views.
Shiraishi
Junji
J
Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, The University of Chicago, MC2026, 5841 S. Maryland Avenue, Chicago, IL 60637, USA. junji@uchicago.edu
Li
Feng
F
Doi
Kunio
K
D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005189:False Positive Reactions; D008171:Lung Diseases / Q000000981:diagnostic imaging; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D013902:Radiography, Thoracic / Q000379:methods*; D012680:Sensitivity and Specificity