PL EN


Preferences help
enabled [disable] Abstract
Number of results
2009 | 116 | 4 | 690-692
Article title

Optical Biopsy Method for Breast Cancer Diagnosis Based on Artificial Neural Network Classification οf Fluorescence Landscape Data

Content
Title variants
Languages of publication
EN
Abstracts
EN
Supervised self-organizing map, a type of artificial neural network, is applied for classification of human breast tissue samples utilizing data obtained from fluorescence landscape measurements. Female breast tissue samples were taken soon after the surgical resection, identified and stored at -80°C until fluorescence measurements. From fluorescence landscapes obtained in UV-VIS region spectral features showing statistically significant differences between malignant and normal samples are identified and further quantified to serve as a training input to neural network. Additional set of samples was used as a test group input to trained network in order to evaluate performance of proposed optical biopsy method. Classification sensitivity of 83.9% and specificity of 88.9% are found.
Keywords
Contributors
  • Institute of Nuclear Sciences "Vinča", University of Belgrade, 11001 Belgrade, Serbia
author
  • Institute of Nuclear Sciences "Vinča", University of Belgrade, 11001 Belgrade, Serbia
  • Institute of Nuclear Sciences "Vinča", University of Belgrade, 11001 Belgrade, Serbia
author
  • Faculty of Mechanical Engineering, University of Belgrade, Kraljice Marije 16, 11120 Belgrade, Serbia
  • Institute of Nuclear Sciences "Vinča", University of Belgrade, 11001 Belgrade, Serbia
References
  • 1. http://www.komen.org/bci (accessed 2009)
  • 2. R.R. Alfano, G.C. Tang, A. Pradhan, W. Lam, D.S.J. Choy, E. Opher, IEEE J. Quantum Electron. 23, 1806 (1987)
  • 3. T. Dramićanin, M.D. Dramićanin, V. Jokanović, D. Nikolić-Vukosavljević, B. Dimitrijević, Photochem. Photobiol. 81, 1554 (2005)
  • 4. K.T. Schomacker, J.K. Frisoli, C.C. Compton, T.J. Flotte, J.M. Richter, N.S. Nishioka, T.F. Deutsch, Lasers Surg. Med. 12, 63 (1992)
  • 5. S.D. Kamath, K.K. Mahato, J. Biomed. Opt. 12, 14028 (2007)
  • 6. H.J.C.M. Sterenborg, M. Motamedi, R.F. Wagner, M. Duvic, S. Thomsen, S.L. Jacques, Lasers Med. Sci. 9, 191 (1994)
  • 7. T. Kohonen, Self-Organizing Maps, 3rd ed., Springer, Berlin 2001
  • 8. T. Kohonen, Computer 21, 11 (1988)
  • 9. H. Motulsky, Intuitive Biostatistics, Oxford University Press, New York 1995
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.bwnjournal-article-appv116n474kz
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.