Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
504484 | Computerized Medical Imaging and Graphics | 2008 | 7 Pages |
Abstract
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%.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Shingo Iwano, Tatsuya Nakamura, Yuko Kamioka, Mitsuru Ikeda, Takeo Ishigaki,