Use of principal component factor analysis in the detection of carotid artery disease from Doppler ultrasound

  • S. B. Sherriff
  • D. C. Barber
  • T. R. P. Martin
  • J. M. Lakeman


Principal component factor analysis, a mathematical feature extraction technique, has been used to analyse the total information contained in the Doppler signal. In this study two patient groups have been investigated, normals and stenoses of less than 50%. The patients have been classified according to angiographic findings (patients with hypertension, migrane, heart disease, etc. havenot been excluded). The results from the principal component analysis technique have been compared with the more familiar A/B ratio based on the maximum frequency enevelope. Of the 25 normal vessel segments 20 were classified as normal by the A/B ratio technique and 22 by the principal component technique, while of the 19 abnormal vessels 13 were classified as abnormal by the A/B technique and 17 by the principal component analysis. Also the principal component analysis of the total Doppler signal was statistically superior to the A/B ratio in separating the two groups examined in this study.


Carotid artery Doppler ultrasound Feature extraction Principal component factor analysis Transient cerebral ischaemia 


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Copyright information

© IFMBE 1982

Authors and Affiliations

  • S. B. Sherriff
    • 1
  • D. C. Barber
    • 1
  • T. R. P. Martin
    • 1
  • J. M. Lakeman
    • 2
  1. 1.Sheffield University and Area Health Authority (Teaching), Department of Medical Physics and Clinical EngineeringRoyal Hallamshire HospitalSheffieldEngland
  2. 2.Sheffield University and Area Health Authority (Teaching), Department of MedicineNorthern General HospitalSheffieldEngland

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