Detection of ophthalmic artery stenosis by least-mean squares backpropagation neural network

Guler İ., Ubeyli E.

COMPUTERS IN BIOLOGY AND MEDICINE, cilt.33, sa.4, ss.333-343, 2003 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 33 Sayı: 4
  • Basım Tarihi: 2003
  • Doi Numarası: 10.1016/s0010-4825(03)00011-8
  • Dergi Adı: COMPUTERS IN BIOLOGY AND MEDICINE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.333-343
  • Gazi Üniversitesi Adresli: Evet

Özet

Doppler ultrasound is a noninvasive technique that allows the examination of the direction, velocity, and volume of blood flow. In this study, ophthalmic artery Doppler signals were obtained from 105 subjects, 48 of whom had suffered from ophthalmic artery stenosis. A least-mean squares backpropagation neural network was used to detect the presence or absence of ophthalmic artery stenosis. Spectral analysis of ophthalmic artery Doppler signals was done by the Welch method for determining the neural network inputs. The network was trained, cross validated and tested with subject records from the database. Performance indicators and statistical measures were used for evaluating the neural network. Ophthalmic artery Doppler signals were classified with the accuracy varying from 88.9% to 90.6%. (C) 2003 Elsevier Science Ltd. All rights reserved.