Automated Lung Nodule Detection at Low-Dose CT: Preliminary Experience |
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Authors: | Jin Mo Goo Jeong Won Lee Hyun Ju Lee Seunghwan Kim Jong Hyo Kim Jung-Gi Im |
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Affiliation: | 1Department of Radiology, Seoul National University College of Medicine, and the Institute of Radiation Medicine, SNUMRC, Korea.;2Human Information Processing Team, Electronics and Telecommunications Research Institute, Korea. |
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Abstract: | ObjectiveTo determine the usefulness of a computer-aided diagnosis (CAD) system for the automated detection of lung nodules at low-dose CT.Materials and MethodsA CAD system developed for detecting lung nodules was used to process the data provided by 50 consecutive low-dose CT scans. The results of an initial report, a second look review by two chest radiologists, and those obtained by the CAD system were compared, and by reviewing all of these, a gold standard was established.ResultsBy applying the gold standard, a total of 52 nodules were identified (26 with a diameter ≤ 5 mm; 26 with a diameter > 5 mm). Compared to an initial report, four additional nodules were detected by the CAD system. Three of these, identified only at CAD, formed part of the data used to derive the gold standard. For the detection of nodules > 5 mm in diameter, sensitivity was 77% for the initial report, 88% for the second look review, and 65% for the CAD system. There were 8.0±5.2 false-positive CAD results per CT study.ConclusionThese preliminary results indicate that a CAD system may improve the detection of pulmonary nodules at low-dose CT. |
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Keywords: | Lung, nodule Lung, CT Computer-aided diagnosis |
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