Abstract
The classification of diffuse lung opacities in high-resolution 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 histogram feature has been shown to be effective. In order to improve further the classification performance of the CAD system, we have proposed the use of a local histogram feature vector. The experimental results show that the proposed method leads to clear improvement of the classification performance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Duncan, J.S., Ayache, N.: Medical image analysis: Progress over two decades and the challenges ahead. IEEE Trans. PAMI-22(1), 85–106 (2000)
Doi, K.: Computer-aided diagnosis in medical imaging: Historical review, current status and future potential. Computerized Medical Imaging and Graphics 31, 198–211 (2007)
Sluimer, I., Schilham, A., Prokop, M., van Ginneken, B.: Computer analysis of computed tomography scans of the lung: A survey. IEEE Trans., Medical Imaging 25(4), 385–405 (2006)
Gabor, D.: Theory of communication. J. Inst. Elect. Engr. 93, 429–457 (1946)
Jain, A.K., Farrokhnia, F.: Unsupervised texture segmentation using Gabor filters. Pattern Recognition 24, 1167–1186 (1991)
Turner, M.R.: Texture discrimination by Gabor functions. Biol. Cybernet. 55, 71–82 (1986)
Mitani, Y., Yasuda, H., Kido, S., Ueda, K., Matsunaga, N., Hamamoto, Y.: Combining the Gabor and histogram features for classifying diffuse lung opacities in thin-section computed tomography. In: Proc. 16th Int. Conf. Pattern Recognition, vol. I, pp. 53–56 (2002)
Mitani, Y., Yasuda, H., Kido, S., Ueda, K., Matsunaga, N., Hamamoto, Y.: Combined features for classifying diffuse lung opacities in thin-section computed tomography images. In: Damiani, E., et al. (eds.) Knowledge-Based Intelligent Information Engineering Systems & Allied Technologies. Frontiers in Artificial Intelligence and Applications, vol. 82, PartI, pp. 121–125. IOS Press (2002)
Devijver, P.A., Kittler, J.: Pattern recognition: A statistical approach. Prentice / Hall (1982)
Fukunaga, K.: Introduction to statistical pattern recognition, 2nd edn. Academic Press (1990)
Mitani, Y., Hamamoto, Y.: Classifier design based on the use of nearest neighbor samples. In: Proc. 15th Int. Conf. Pattern Recognition, vol. 2, pp. 773–776 (2000)
Mitani, Y., Hamamoto, Y.: A local mean-based nonparametric classifier. Pattern Recognition Letters 27(10), 1151–1159 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mitani, Y., Fujita, Y., Matsunaga, N., Hamamoto, Y. (2012). The Use of a Local Histogram Feature Vector of Classifying Diffuse Lung Opacities in High-Resolution Computed Tomography. In: Jiang, H., Ding, W., Ali, M., Wu, X. (eds) Advanced Research in Applied Artificial Intelligence. IEA/AIE 2012. Lecture Notes in Computer Science(), vol 7345. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31087-4_36
Download citation
DOI: https://doi.org/10.1007/978-3-642-31087-4_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31086-7
Online ISBN: 978-3-642-31087-4
eBook Packages: Computer ScienceComputer Science (R0)