Validation of an optical flow algorithm to measure blood flow waveforms in arteries using dynamic digital X-ray images

Rhode, Kawal, Lambrou, T., Hawkes, David J. , Hamilton, George and Seifalian, Alexander M. (2000) Validation of an optical flow algorithm to measure blood flow waveforms in arteries using dynamic digital X-ray images. In: SPIE Medical Imaging 2000, 14 - 17 February 2000, San Diego, California.

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive


We have developed a weighted optical flow algorithm for the extraction of instantaneous blood velocity from dynamic digital x-ray images of blood vessels. We have carried out in-vitro validation of this technique. A pulsatile physiological blood flow circuit was constructed using sections of silicone tubing to simulate blood vessels with whole blood as the fluid. Instantaneous recording of flow from an electromagnetic flow meter (EMF) provided the gold standard measurement. Biplanar dynamic digital x-ray images of the blood vessel with injection of contrast medium were acquired at 25 fps using a PC frame capture card. Imaging of a Perspex calibration cube allowed 3D reconstruction of the vessel and determination of true dimensions. Blood flow waveforms were calculated off-line on a Sun workstation using the new algorithm. The correlation coefficient between instantaneous blood flow values obtained from the EMF and the x-ray method was r = 0.871, n = 1184, p<0.0001. The correlation coefficient for average blood flow was r = 0.898, n = 16, p<0.001. We have successfully demonstrated that our new algorithm can measure pulsatile blood flow in a vessel phantom. We aim to use this algorithm to measure blood flow clinically in patients undergoing vascular interventional procedures.

Additional Information:Conference Code: 57071
Keywords:Algorithms, Angiography, Blood vessels, Flow measurement, Hemodynamics, Optical flows, Pulsatile flow, Waveform analysis, Digital X ray imaging, Electromagnetic flow meters, X ray radiography
Subjects:F Physical Sciences > F350 Medical Physics
G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
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ID Code:8679
Deposited On:13 May 2013 11:46

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