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Proceedings Paper

Effect of quantization on co-occurrence matrix based texture features: an example study in mammography
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Paper Abstract

A co-occurrence matrix is a joint probability distribution of the pixel values of two pixels in an image separated by a distance d in the direction θ. It is one of the texture analysis tools favored by the medical image processing community. The size of a co-occurrence matrix depends on gray levels re-quantization Q. Hence, when dealing with high depth resolution images, gray levels re-quantization is routinely performed to reduce the size of the co-occurrence matrix. The gray levels re-quantization may play a role in the display of spatial relationships in co-occurrence matrix but is usually dealt with lightly. In this paper, we use an example to study the effect of gray-level re-quantization in high depth resolution medical images. Digitized film-screen mammograms have a typical depth resolution of 4096 gray levels. In a study classifying masses on mammograms as benign or malignant, 260 texture features are measured on 43 regions-of-interest (ROIs) containing malignant masses and 28 ROIs containing benign masses. Of the 260 texture features, 240 are texture features measured on co-occurrence matrices with parameters θ = 0, π/2; d = 11, 15, 21, 25, 31; and Q = 50, 100, 400. A genetic algorithm is used to select a subset of features (out of 260) that has discriminative power. Results show that top performing feature combinations selected by the genetic algorithm are not restricted to a single value of Q. This indicates that instead of searching for a correct Q, it may be more appropriate to explore a range of Q values.

Paper Details

Date Published: 15 March 2006
PDF: 9 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61445C (15 March 2006);
Show Author Affiliations
Gobert N. Lee, Gifu Univ. (Japan)
Flinders Univ. (Australia)
Murk J. Bottema, Flinders Univ. (Australia)
Takeshi Hara, Gifu Univ. (Japan)
Hiroshi Fujita, Gifu Univ. (Japan)

Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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