A multiscale Laplacian of Gaussian filtering approach to automated pulmonary nodule detection from whole-lung low-dose CT scans

Sergei V. Fotin; Anthony P. Reeves; Alberto M. Biancardi; David F. Yankelevitz; Claudia I. Henschke

doi:10.1117/12.811420

3 March 2009 A multiscale Laplacian of Gaussian filtering approach to automated pulmonary nodule detection from whole-lung low-dose CT scans

Sergei V. Fotin, Anthony P. Reeves, Alberto M. Biancardi, David F. Yankelevitz, Claudia I. Henschke

Author Affiliations +

Proceedings Volume 7260, Medical Imaging 2009: Computer-Aided Diagnosis; 72601Q (2009) https://doi.org/10.1117/12.811420
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

The primary stage of a pulmonary nodule detection system is typically a candidate generator that efficiently provides the centroid location and size estimate of candidate nodules. A scale-normalized Laplacian of Gaussian (LOG) filtering method presented in this paper has been found to provide high sensitivity along with precise locality and size estimation. This approach involves a computationally efficient algorithm that is designed to identify all solid nodules in a whole lung anisotropic CT scan. This nodule candidate generator has been evaluated in conjunction with a set of discriminative features that target both isolated and attached nodules. The entire detection system was evaluated with respect to a sizeenriched dataset of 656 whole-lung low-dose CT scans containing 459 solid nodules with diameter greater than 4 mm. Using a soft margin SVM classifier, and setting false positive rate of 10 per scan, we obtained a sensitivity of 97% for isolated, 93% for attached, and 89% for both nodule types combined. Furthermore, the LOG filter was shown to have good agreement with the radiologist ground truth for size estimation.

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Sergei V. Fotin, Anthony P. Reeves, Alberto M. Biancardi, David F. Yankelevitz, and Claudia I. Henschke "A multiscale Laplacian of Gaussian filtering approach to automated pulmonary nodule detection from whole-lung low-dose CT scans", Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72601Q (3 March 2009); https://doi.org/10.1117/12.811420

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