Divergence Compensatory Optical Flow Method for Blood Velocimetry

Author:

Yang Zifeng1,Yu Hongtao2,Huang George P.3,Ludwig Bryan45

Affiliation:

1. Mem. ASME Department of Mechanical and Materials Engineering, Wright State University, 3640 Colonel Glenn Highway, Dayton, OH 45435 e-mail:

2. Department of Mechanical and Materials Engineering, Wright State University, Dayton, OH 45435 e-mail:

3. Fellow ASME Department of Mechanical and Materials Engineering, Wright State University, Dayton, OH 45435 e-mail:

4. Boonshoft School of Medicine, Wright State University, Dayton, OH 45435;

5. Division of NeuroInterventional Surgery, Department of Neurology, Premier Health—Clinical Neuroscience Institute, Wright State University, 30 E. Apple Street, Dayton, OH 45409 e-mail:

Abstract

Detailed blood velocity map in the vascular system can be obtained by applying the optical flow method (OFM) in processing fluoroscopic digital subtracted catheter angiographic images; however, there are still challenges with the accuracy of this method. In the present study, a divergence compensatory optical flow method (DC-OFM), in which a nonzero divergence of velocity is assumed due to the finite resolution of the image, was explored and applied to the digital subtraction angiography (DSA) images of blood flow. The objective of this study is to examine the applicability and evaluate the accuracy of DC-OFM in assessing the blood flow velocity in vessels. First, an Oseen vortex flow was simulated on the standard particle image to generate an image pair. Then, the DC-OFM was applied on the particle image pair to recover the velocity field for validation. Second, DSA images of intracranial arteries were used to examine the accuracy of the current method. For each set of images, the first image is the in vivo DSA image, and the second image is generated by superimposing a given flow field. The recovered velocity map by DC-OFM agrees well with the exact velocity for both the particle images and the angiographic images. In comparison with the traditional OFM, the present method can provide more accurate velocity estimation. The accuracy of the velocity estimation can also be improved by implementing preprocess techniques including image intensification, Gaussian filtering, and “image-shift.”

Publisher

ASME International

Subject

Physiology (medical),Biomedical Engineering

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