Paper
18 January 2006 T-ray relevant frequencies for osteosarcoma classification
W. Withayachumnankul, B. Ferguson, T. Rainsford, D. Findlay, S. P. Mickan, D. Abbott
Author Affiliations +
Proceedings Volume 6038, Photonics: Design, Technology, and Packaging II; 60381H (2006) https://doi.org/10.1117/12.637964
Event: Microelectronics, MEMS, and Nanotechnology, 2005, Brisbane, Australia
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.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
W. Withayachumnankul, B. Ferguson, T. Rainsford, D. Findlay, S. P. Mickan, and D. Abbott "T-ray relevant frequencies for osteosarcoma classification", Proc. SPIE 6038, Photonics: Design, Technology, and Packaging II, 60381H (18 January 2006); https://doi.org/10.1117/12.637964
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Cited by 9 scholarly publications.
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KEYWORDS
Terahertz radiation

Feature selection

Bone

Feature extraction

Picosecond phenomena

Spectroscopy

Signal attenuation

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