Analysis of a three-dimensional lung nodule detection method for thoracic CT scans

Samuel G. Armato III; Maryellen Lissak Giger; Heber MacMahon

doi:10.1117/12.387742

6 June 2000 Analysis of a three-dimensional lung nodule detection method for thoracic CT scans

Samuel G. Armato III, Maryellen Lissak Giger, Heber MacMahon

Proceedings Volume 3979, Medical Imaging 2000: Image Processing; (2000) https://doi.org/10.1117/12.387742
Event: Medical Imaging 2000, 2000, San Diego, CA, United States

Abstract

We are developing an automated method to analyze the three- dimensional nature of structures within CT scans and identify those structures that represent lung nodules. The set of segmented lung regions from all sections of a CT scan forms a segmented lung volume within which multiple gray-level thresholds are applied. Contiguous three-dimensional structures are identified within each thresholded lung volume, and structures that satisfy a volume criterion constitute an initial set of nodule candidates. A feature vector is then computed for each nodule candidate. A rule-based scheme is applied to the initial candidate set to reduce the number of nodule candidates that correspond to normal anatomy. Feature vectors for the remaining candidates are merged through an automated classifier to further distinguish between candidates that correspond to nodules and candidates that correspond to normal structures. This automated method demonstrates promising performance in its ability to detect lung nodules in CT images. Such a technique may assist radiologists evaluate, for example, images from low-dose, screening thoracic CT examinations.

Citation Download Citation

Samuel G. Armato III, Maryellen Lissak Giger, and Heber MacMahon "Analysis of a three-dimensional lung nodule detection method for thoracic CT scans", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); https://doi.org/10.1117/12.387742

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