Abstract
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 practical situations such that the ratio of the dimensionality to the training sample size per a class is small, the design of a CAD system for classifying diffuse lung opacities is considered to be one of difficult tasks. In this paper, we examine the classification performance of nonparametric classifiers for a CAD system of diffuse lung opacities in practical situations.
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Mitani, Y., Fujita, Y., Matsunaga, N., Hamamoto, Y. (2004). A Study on Nonparametric Classifiers for a CAD System of Diffuse Lung Opacities in Thin-Section Computed Tomography Images. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30132-5_84
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DOI: https://doi.org/10.1007/978-3-540-30132-5_84
Publisher Name: Springer, Berlin, Heidelberg
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