Journal
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
Volume 32, Issue 5, Pages 416-422Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compmedimag.2008.04.001
Keywords
computer-aided diagnosis (CAD); high-resolution CT (HRCT); lung cancer; pulmonary nodules
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We investigated the possibility of using computer analysis of high-resolution CT images to radiologically classify the shape of pulmonary nodules. From a total of 107 HRCT images of solid, solitary pulmonary nodules with prior differentiation as benign (n=55) or malignant (n=52), we extracted the desired pulmonary nodules and calculated two quantitative parameters for characterizing nodules: circularity and second central moment. Using discriminant analysis for two thresholds in differentiating malignant from benign states resulted in a sensitivity of 76.9%, a specificity of 80%, a positive predictive value of 78.4%, and a negative predictive value of 78.6%. (c) 2008 Elsevier Ltd. All rights reserved.
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