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Technical Developments |
1 From the Department of Radiology, David Geffen School of Medicine at UCLA, 10833 Le Conte Ave, Los Angeles, CA 90095-1721. Received October 18, 2001; revision requested January 11, 2002; revision received March 11; accepted May 7, 2002. Address correspondence to M.S.B. (e-mail: mbrown@mednet.ucla.edu).
An automated system was developed for detecting lung micronodules on thin-section computed tomographic images and was applied to data from 15 subjects with 77 lung nodules. The automated system, without user interaction, achieved a sensitivity of 100% for nodules (>3 mm in diameter) and 70% for micronodules (
3 mm). With the same images, a radiologist detected nodules and micronodules with sensitivities of 91% and 51%, respectively, without system input. With assistance from the automated system, these sensitivities increased to 95% and 74%, respectively. Preliminary results indicate that the automated system considerably improved the radiologist’s performance in micronodule detection.
© RSNA, 2002
Index terms: Computed tomography (CT), computer programs • Computed tomography (CT), image processing • Computers, diagnostic aid • Lung, nodule, 60.281
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