| Autor: |
van Staveren HJ; Department of Clinical Physics, PDT Laboratory, Daniel den Hoed Cancer Center, University Hospital Rotterdam, PO Box 5201, NL-3008 AE, Rotterdam, Netherlands., van Veen RL, Speelman OC, Witjes MJ, Star WM, Roodenburg JL |
| Jazyk: |
angličtina |
| Zdroj: |
Oral oncology [Oral Oncol] 2000 May; Vol. 36 (3), pp. 286-93. |
| DOI: |
10.1016/s1368-8375(00)00004-x |
| Abstrakt: |
The performance of an artificial neural network was evaluated as an alternative classification technique of autofluorescence spectra of oral leukoplakia, which may reflect the grade of tissue dysplasia. Twenty-two visible lesions of 21 patients suffering from oral leukoplakia and six locations on normal oral mucosa of volunteers were investigated with autofluorescence spectroscopy (420 nm excitation, 465-650 nm emission). Pre-scaled spectra were combined with the corresponding visual and histopathological classifications in order to train artificial neural networks. A trained network is mapping input spectra to tissue characteristics, which was evaluated using a blind set of spectra. Abnormal tissue could be distinguished from normal tissue by a neural network with a sensitivity of 86% and a specificity of 100%. Also, classifying either homogeneous or non-homogeneous tissue performed reasonably well. Weak or no correlation existed between spectral patterns and verrucous or erosive tissue or the grade of dysplasia, hyperplasia and hyperkeratosis. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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