Journal
ULTRASOUND IN MEDICINE AND BIOLOGY
Volume 28, Issue 2, Pages 209-216Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/S0301-5629(01)00505-1
Keywords
online artery diameter measurement; flow-mediated dilation; artificial neural network; ultrasound image; virtual ultrasound scanner
Ask authors/readers for more resources
An automated online technique is described for measurement of artery diameter in flow-mediated dilation (FMD) ultrasound (US) images, using artificial neural networks to identify and track artery walls. This allows FMD results to be calculated without the inherent delay of current retrospective methods. Two networks were trained to identify artery anterior and posterior walls using over 3200 examples from carotid artery images. Both networks correctly classified approximately 97% of the randomly selected test samples. The technique was verified using a physical model with absolute measurement error of -1.16% +/- 1.04% (mean SD) over the diameter range 2 to 8 mm. Advantages of the technique include: online analysis; wall tracking optimisation before the study proper; measurement of diameter changes over the cardiac cycle; low FMD measurement variance; minimal image degradation; and no unwieldy image store. Measurement of artery diameter changes over the cardiac cycle was explored using simulated image sequences generated with a virtual US scanner. (C) 2002 World Federation for Ultrasound in Medicine Biology.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available