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Computerized Detection of Pulmonary Nodules on CT Scans¹

¹ From the Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, MC 2026, University of Chicago, 5841 S Maryland Ave, Chicago, IL 60637. Recipient of an Excellence in Design award for a scientific exhibit at the 1998 RSNA scientific assembly. Received February 15, 1999; revision requested March 18 and received May 4; accepted May 7. Supported in part by grants CA48985, CA62625, CA64370, and RR11459 from the U.S. Public Health Service; funding from the University of Chicago Cancer Research Center; and a grant from the American Lung Association of Metropolitan Chicago. Address reprint requests to S.G.A.

Helical computed tomography (CT) is the most sensitive imaging modality for detection of pulmonary nodules. However, a single CT examination produces a large quantity of image data. Therefore, a computerized scheme has been developed to automatically detect pulmonary nodules on CT images. This scheme includes both two- and three-dimensional analyses. Within each section, gray-level thresholding methods are used to segment the thorax from the background and then the lungs from the thorax. A rolling ball algorithm is applied to the lung segmentation contours to avoid the loss of juxtapleural nodules. Multiple gray-level thresholds are applied to the volumetric lung regions to identify nodule candidates. These candidates represent both nodules and normal pulmonary structures. For each candidate, two- and three-dimensional geometric and gray-level features are computed. These features are merged with linear discriminant analysis to reduce the number of candidates that correspond to normal structures. This method was applied to a 17-case database. Receiver operating characteristic (ROC) analysis was used to evaluate the automated classifier. Results yielded an area under the ROC curve of 0.93 in the task of classifying candidates detected during thresholding as nodules or nonnodules.

Index Terms: Computed tomography (CT), computer programs • Computed tomography (CT), image processing • Computers, diagnostic aid • Lung, nodule, 60.281

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