Berry, E., Handley, J.W., Fitzgerald, A.J. et al. (6 more authors) (2004) Multispectral classification techniques for terahertz pulsed imaging: an example in histopathology. Medical Engineering and Physics, 26 (5). pp. 423-430. ISSN 1350-4533
Abstract
Terahertz pulsed imaging is a spectroscopic imaging modality using pulses of electromagnetic radiation (100 GHz to 10 THz), and there has been recent interest in studying biomedical specimens. It is usual to display parametric images derived from the measured pulses. In this work, classification was achieved by applying multispectral clustering techniques to sets of parametric images. It was hypothesised that adequate information for clustering was carried in a small number of parametric images, providing these were weighted by complementary physical properties. Materials prepared for histopathological examination were chosen because their condition remained stable during long imaging periods and because their dehydrated state led to greater penetration of the radiation. Two specimens were examined in this pilot study, one of basal cell carcinoma and one of melanoma. Unsupervised ISODATA classification using three selected parametric terahertz pulsed images was compared qualitatively with k-means classification using the shape of the whole time series, and with conventional stained microscope slides. There was good qualitative agreement between the classifications. Classifications were consistent with the morphological appearances expected, but further work is required to determine if tumour discrimination is possible. The results have implications for the future development of the technique as the need for only a small number of features could lead to considerably reduced acquisition times.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Copyright © 2004 IPEM. |
Keywords: | terahertz pulsed imaging, multispectral classification, clustering, histopathology, basal cell carcinoma, melanoma |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Genetics, Health and Therapeutics (LIGHT) > Academic Unit of Medical Physics (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Pollard Institute (Leeds) |
Depositing User: | Elizabeth Berry |
Date Deposited: | 13 Mar 2006 |
Last Modified: | 25 Oct 2016 08:25 |
Published Version: | http://dx.doi.org/10.1016/j.medengphy.2004.02.011 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1016/j.medengphy.2004.02.011 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:670 |