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Fractal texture analysis in computer-aided diagnosis of solitary pulmonary nodules
N F Vittitoe1, J A Baker, C E Floyd
1Department of Biomedical, Engineering, Duke University, Durham, NC 27710, USA.
Rationale And Objectives:
The authors investigated the use of fractal texture characterization to improve the accuracy of solitary pulmonary nodule computer-aided diagnosis (CAD) systems.
Methods:
Thirty chest radiographs were acquired from patients who had no pulmonary nodules. Thirty regions were selected that were considered remotely suspicious-looking for nodules. Artificial nodules of multiple shapes, sizes, and orientations were added at subtle levels of contrast to 30 non-suspicious-looking regions of the radiographs. Fractal dimensions of the 60 "nodule candidates" were calculated to quantify the texture of each region. Four radiologists also interpreted the images.
Results:
The fractal dimension of each possible nodule provided statistically significant (P < .05) differentiation between regions that contained an artificial nodule and those that did not. The area under the receiver operating characteristic curve for the fractal analysis was significantly better (P < .05) than that for the radiologists.
Conclusion:
Fractal texture characterization provides useful information for the classification of potential solitary pulmonary nodules with CAD algorithms.