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Proceedings Paper

T-ray relevant frequencies for osteosarcoma classification
Author(s): W. Withayachumnankul; B. Ferguson; T. Rainsford; D. Findlay; S. P. Mickan; D. Abbott
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Paper Abstract

We investigate the classification of the T-ray response of normal human bone cells and human osteosarcoma cells, grown in culture. Given the magnitude and phase responses within a reliable spectral range as features for input vectors, a trained support vector machine can correctly classify the two cell types to some extent. Performance of the support vector machine is deteriorated by the curse of dimensionality, resulting from the comparatively large number of features in the input vectors. Feature subset selection methods are used to select only an optimal number of relevant features for inputs. As a result, an improvement in generalization performance is attainable, and the selected frequencies can be used for further describing different mechanisms of the cells, responding to T-rays. We demonstrate a consistent classification accuracy of 89.6%, while the only one fifth of the original features are retained in the data set.

Paper Details

Date Published: 18 January 2006
PDF: 15 pages
Proc. SPIE 6038, Photonics: Design, Technology, and Packaging II, 60381H (18 January 2006); doi: 10.1117/12.637964
Show Author Affiliations
W. Withayachumnankul, King Mongkut's Institute of Technology Ladkrabang (Thailand)
The Univ. of Adelaide (Australia)
B. Ferguson, Tenix Systems Pty. Ltd. (Australia)
The Univ. of Adelaide (Australia)
T. Rainsford, The Univ. of Adelaide (Australia)
D. Findlay, The Univ. of Adelaide (Australia)
S. P. Mickan, The Univ. of Adelaide (Australia)
D. Abbott, The Univ. of Adelaide (Australia)


Published in SPIE Proceedings Vol. 6038:
Photonics: Design, Technology, and Packaging II
Derek Abbott; Yuri S. Kivshar; Halina H. Rubinsztein-Dunlop; Shanhui Fan, Editor(s)

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