Show simple item record

dc.creatorLenhardt, Lea I.
dc.creatorZeković, Ivana Lj.
dc.creatorDramićanin, Tatjana
dc.creatorDramićanin, Miroslav
dc.identifier.issn0031-8949 (print)
dc.identifier.issn1402-4896 (electronic)
dc.description.abstractOver the years various optical spectroscopic techniques have been widely used as diagnostic tools in the discrimination of many types of malignant diseases. Recently, synchronous fluorescent spectroscopy (SFS) coupled with chemometrics has been applied in cancer diagnostics. The SFS method involves simultaneous scanning of both emission and excitation wavelengths while keeping the interval of wavelengths (constant-wavelength mode) or frequencies (constant-energy mode) between them constant. This method is fast, relatively inexpensive, sensitive and non-invasive. Total synchronous fluorescence spectra of normal skin, nevus and melanoma samples were used as input for training of artificial neural networks. Two different types of artificial neural networks were trained, the self-organizing map and the feed-forward neural network. Histopathology results of investigated skin samples were used as the gold standard for network output. Based on the obtained classification success rate of neural networks, we concluded that both networks provided high sensitivity with classification errors between 2 and 4%.en
dc.relationinfo:eu-repo/grantAgreement/MESTD/Integrated and Interdisciplinary Research (IIR or III)/45020/RS//
dc.relationinfo:eu-repo/grantAgreement/MESTD/Basic Research (BR or ON)/173049/RS//
dc.sourcePhysica Scriptaen
dc.titleArtificial neural networks for processing fluorescence spectroscopy data in skin cancer diagnosticsen
dcterms.abstractДрамићанин Мирослав; Ленхардт-Aцковић Леа; Зековић ивана; Драмићанин Татјана;
dc.citation.otherArticle Number: 014057
dc.description.other3rd International Conference on the Physics of Optical Materials and Devices, Sep 02-06, 2012, Belgrade, Serbiaen

Files in this item


There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record