Classification of terahertz data as a tool for the detection of cancer

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dc.contributor.authorBerryman, M.
dc.contributor.authorRainsford, T.
dc.contributor.conferenceBiomedical Applications of Micro- and Nanoengineering (3rd : 2006 : Adelaide, Australia)
dc.contributor.editorNicolau, D.
dc.date.issued2006
dc.descriptionCopyright © 2006 SPIE--The International Society for Optical Engineering
dc.description.abstractThe early detection of cancers is critical with respect to treatment and patient survival. Biopsy techniques that are currently employed for such diagnoses are invasive, time consuming and costly. A Terahertz (THz) imaging system potentially provides a fast and non-invasive way to detect and diagnose cancer. While there is proof of concept that THz can distinguish cancerous and normal tissue, the mechanisms underlying this differentiation are not well understood. A better understanding of THz spectral data can be gained through computational pattern recognition and related multivariate statistical tools. These allow for the differentiation of data into discrete and disjoint groups. Such separation of THz spectral data can provide complex information about diseased tissue, which can be used as a tool for distinguishing cancerous from non-cancerous cells as well as, discriminating between cancers at various developmental stages and, between different types of cancer.
dc.identifier.citationBiomedical Applications of Micro- and Nanoengineering III / Dan V. Nicolau (ed.)
dc.identifier.doi10.1117/12.695693
dc.identifier.issn0277-786X
dc.identifier.urihttp://hdl.handle.net/2440/35265
dc.language.isoen
dc.publisherSPIE
dc.publisher.placeUSA
dc.relation.ispartofseriesProceedings of SPIE ; 6416
dc.source.urihttp://dx.doi.org/10.1117/12.695693
dc.titleClassification of terahertz data as a tool for the detection of cancer
dc.typeConference paper
pubs.publication-statusPublished

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