Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6337
Title: Automatic detection of ophthalmic artery stenosis using the adaptive neuro-fuzzy inference system
Authors: Güler, İnan
Übeyli, Derya Elif
Keywords: adaptive neuro-fuzzy inference system (ANFIS)
fuzzy logic
doppler signal
ophthalmic artery stenosis
Issue Date: 2005
Publisher: Pergamon-Elsevier Science Ltd
Abstract: In this study, a new approach based on an adaptive neuro-fuzzy inference system (ANFIS) was presented for detection of ophthalmic artery stenosis. The ANFIS was used to detect ophthalmic artery stenosis when two features, resistivity and pulsatility indices, defining changes of ophthalmic arterial Doppler waveforms were used as inputs. The ophthalmic arterial Doppler signals were recorded from 115 subjects, of whom 52 suffered from ophthalmic artery stenosis and the rest were healthy. The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach. Some conclusions concerning the impacts of features on the detection of ophthalmic artery stenosis were obtained through analysis of the ANFIS. The performances of the classifiers were evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS classifier has potential in detecting the ophthalmic artery stenosis. (c) 2004 Elsevier Ltd. All rights reserved.
URI: https://doi.org/10.1016/j.engappai.2004.10.002
https://hdl.handle.net/20.500.11851/6337
ISSN: 0952-1976
1873-6769
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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