Lung Nodule Detection in CT Scans
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Lung Nodule Detection in CT Scans

Authors: M. Antonelli, G. Frosini, B. Lazzerini, F. Marcelloni

Abstract:

In this paper we describe a computer-aided diagnosis (CAD) system for automated detection of pulmonary nodules in computed-tomography (CT) images. After extracting the pulmonary parenchyma using a combination of image processing techniques, a region growing method is applied to detect nodules based on 3D geometric features. We applied the CAD system to CT scans collected in a screening program for lung cancer detection. Each scan consists of a sequence of about 300 slices stored in DICOM (Digital Imaging and Communications in Medicine) format. All malignant nodules were detected and a low false-positive detection rate was achieved.

Keywords: computer assisted diagnosis, medical imagesegmentation, shape recognition.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1332972

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References:


[1] S. Sone, S. Takashima, F. Li, Z. Yang, T. Honda, Y. Maruyama, M. Hasegawa, T. Yamanda, K. Kubo, K. Hanamura, K. Asakura, ''Mass screening for lung cancer with mobile spiral computed tomography scanner'', The Lancet, vol. 351, April 1998, pp. 1242-1245.
[2] T. Nawa, T. Nakagawa, S. Kusano, Y. Kawasaki, Y. Sugawara, H. Nakata, ''Lung cancer screening using low-dose spiral CT: results of baseline and 1-year follow-up studies'', Chest, vol. 122, n.v1, July 2002, pp. 15-20.
[3] M.J.R. Dalrymple-Hay, N.E. Drury, ''Screening for lung cancer'', Journal of the Royal Society of Medicine, vol. 94, January 2001, pp. 2-5.
[4] S. Hu, E.A. Hoffman, J.M. Reinhardt, ''Automatic lung segmentation for accurate quantitation of volumetric x-ray CT images'', IEEE Trans. Medical Imaging, vol. 20, n. 6, June 2001, pp. 490-498.
[5] K.R. Castleman, ''Digital Image Processing'', Prentice Hall, Englewood Cliffs, NJ, USA (1996).
[6] P.S.P. Wang, Y.Y. Zhang, ''A fast and flexible thinning algorithm'', IEEE Trans. Computers, vol. 38, n. 5, May 1989, pp. 741-745.
[7] J. Dehmeshki, X. Ye, J. Costello, ''Shape based region growing using derivatives of 3D medical images: Application to semi-automated detection of pulmonary modules'', International Conference on Image Processing, vol. 1, 2003, pp. 1085-1088.