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Advanced Image Analysis Tools Development for the Early Stage Bronchial Cancer Detection

Authors: P. Bountris, E. Farantatos, N. Apostolou


Autofluorescence (AF) bronchoscopy is an established method to detect dysplasia and carcinoma in situ (CIS). For this reason the “Sotiria" Hospital uses the Karl Storz D-light system. However, in early tumor stages the visualization is not that obvious. With the help of a PC, we analyzed the color images we captured by developing certain tools in Matlab®. We used statistical methods based on texture analysis, signal processing methods based on Gabor models and conversion algorithms between devicedependent color spaces. Our belief is that we reduced the error made by the naked eye. The tools we implemented improve the quality of patients' life.

Keywords: Digital Image Processing, Bronchoscopy, Texture Analysis, lung cancer

Digital Object Identifier (DOI):

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[1] H. van den Bergh, "Early Detection of Lung Cancer and the Role of Endoscopic Fluorescence Imaging", Med. Laser Appl. 18: 20-26, pp 20- 26, 2003.
[2] E. Passalidou, "Early Detection of the Lung Cancer", Pneumon vol. 3, issue 15, Sept-Dec 2002.
[3] N. Apostolou, M. Haritou, N. Lolis, D. Beldekis, A. Rasidakis, D. Koutsouris, "Advanced Platform for Lung Cancer Detection in Autofluorescence Bronchoscopy Images. Clinical Application at the "Sotiria" Hospital, Hellas", J. Qual. Life Res., pg. 154-160, vol. 3, issue 2, 2005.
[4] R. C. Gonzalez, R. E. Woods, S. L. Eddins, Digital Image Processing Using Matlab. New Jersey: Ed. Pearson Prentice Hall, 2004.
[5] R. C. Gonzalez, R. E. Woods, Digital Image Processing, Addison- Wesley Publ. Co., 1993.
[6] M. Tuceryan, A. K. Jain, The Handbook of Pattern Recognition and Computer Vision, World Scientific Publishing Co., 1998, ch.2.1
[7] A. Zizzari, U. Seiffert, B. Michaelis, G. Gademann, S. Swiderski, "Detection of Tumor in Digital Images of the Brain" in Proc. IASTEC International Conference Signal Processing Pattern Recognition & Applications, Rhodes, Greece, 2001, pp. 132-137.
[8] P. Kruizinga, N. Petkov, S. E. Grigorescu "Comparison of Texture Features Based on Gabor Filters," in Proc. 10th International Conference on Image Analysis and Processing, Venice, Italy, 1999, pp. 142-147.