Combining the Gabor and Histogram Features for Classifying Diffuse Lung Opacities in Thin-Section Computed Tomography

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http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1044587

16th International Conference on Patt ...

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	ASCII Text	x
	Y. Mitani, H. Yasuda, S. Kido, K. Ueda, N. Matsunaga, Y. Hamamoto, "Combining the Gabor and Histogram Features for Classifying Diffuse Lung Opacities in Thin-Section Computed Tomography," Pattern Recognition, International Conference on, vol. 1, pp. 10053, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 1, 2002.

	BibTex	x
	@article{ 10.1109/ICPR.2002.1044587, author = {Y. Mitani and H. Yasuda and S. Kido and K. Ueda and N. Matsunaga and Y. Hamamoto}, title = {Combining the Gabor and Histogram Features for Classifying Diffuse Lung Opacities in Thin-Section Computed Tomography}, journal ={Pattern Recognition, International Conference on}, volume = {1}, year = {2002}, issn = {1051-4651}, pages = {10053}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1044587}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Pattern Recognition, International Conference on TI - Combining the Gabor and Histogram Features for Classifying Diffuse Lung Opacities in Thin-Section Computed Tomography SN - 1051-4651 SP EP A1 - Y. Mitani, A1 - H. Yasuda, A1 - S. Kido, A1 - K. Ueda, A1 - N. Matsunaga, A1 - Y. Hamamoto, PY - 2002 KW - null VL - 1 JA - Pattern Recognition, International Conference on ER -

Y. Mitani, Yamaguchi Junior College

H. Yasuda, Yamaguchi University

S. Kido, Yamaguchi University

K. Ueda, Yamaguchi University

N. Matsunaga, Yamaguchi University

Y. Hamamoto, Yamaguchi Junior College

The classification of diffuse lung opacities in thin-section computed tomography (HRCT) images is an important step for developing a computer-aided diagnosis (CAD) system. In designing the CAD system for classifying diffuse lung opacities in HRCT images, a Gabor filter-based approach has been shown to be effective. In order to improve further the classification performance of the CAD system, we explore the combination of the Gabor and histogram features. The ex-perimental results show that combining the Gabor and histogram features leads to clear improvement of the classification performance.

Citation:

Y. Mitani, H. Yasuda, S. Kido, K. Ueda, N. Matsunaga, Y. Hamamoto, "Combining the Gabor and Histogram Features for Classifying Diffuse Lung Opacities in Thin-Section Computed Tomography," icpr, vol. 1, pp.10053, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 1, 2002

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