Experimental estimation of blood flow velocity through simulation of intravital microscopic imaging in micro-vessels by different image processing methods.

Quantization of red blood cell (RBC) velocity in micro-vessel is one of the techniques for dynamic observation of microvascular mechanisms. The flow measurement of RBC in micro-vessels is still a challenge nowadays. Image processing for velocity measurement using a frame by frame analysis is a common approach. The accuracy of the calculations, which is algorithm dependant, has rarely been examined. In this paper, we evaluated the accuracy of the existing methods, which includes cross correlation method, Hough transform method, and optical flow method, by applying these methods to simulated micro-vessel image sequences. Simulated experiments in various micro-vessels with random RBC motion were applied in the evaluation. The blood flow variation in the same micro-vessels with different RBC densities and velocities was considered in the simulations. The calculation accuracy of different flow patterns and vessel shapes were also examined, respectively. Based on the comparison, the use of an optical flow method, which is superior to a cross-correlation method or a Hough transform method, is proposed for measuring RBC velocity. The study indicated that the optical flow method is suitable for accurately measuring the velocity of the RBCs in small or large micro-vessels.

[1]  W Siegenthaler,et al.  Red blood cell velocity in nailfold capillaries of man measured by a television microscopy technique. , 1974, Microvascular research.

[2]  L. Incandela,et al.  Pressure and Microcirculatory Effects of Treatment with Lercanidipine in Hypertensive Patients and in Vascular Patients with Hypertension , 2000, Angiology.

[3]  K. Tsukada,et al.  Image correlation method for measuring blood flow velocity in microcirculation: correlation 'window' simulation and in vivo image analysis. , 2000, Physiological measurement.

[4]  G Coppini,et al.  Different flowmotion patterns in healthy controls and patients with Raynaud's phenomenon. , 1999, Technology and health care : official journal of the European Society for Engineering and Medicine.

[5]  Y. Sugii,et al.  In vivo PIV measurement of red blood cell velocity field in microvessels considering mesentery motion. , 2002, Physiological measurement.

[6]  Geoffrey G. Zhang,et al.  Intrathoracic tumour motion estimation from CT imaging using the 3D optical flow method. , 2004, Physics in medicine and biology.

[7]  C H Chang,et al.  Use of dynamic capillaroscopy for studying cutaneous microcirculation in patients with diabetes mellitus. , 1997, Microvascular research.

[8]  Bronislaw Grzegorzewski,et al.  Estimation of red blood cell aggregate velocity during sedimentation using the Hough transform , 2008 .

[9]  M. Gomes,et al.  Endothelial function in patients with type 1 diabetes evaluated by skin capillary recruitment. , 2007, Microvascular research.

[10]  R. Mattace,et al.  Nail-fold capillaroscopy in the study of microcirculation in elderly hypertensive patients. , 1996, Archives of gerontology and geriatrics.

[11]  Geoffrey Zhang,et al.  Red blood cell velocity measurements of complete capillary in finger nail-fold using optical flow estimation. , 2009, Microvascular research.

[12]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[13]  Geoffrey G. Zhang,et al.  Semi-automated CT segmentation using optic flow and Fourier interpolation techniques , 2006, Comput. Methods Programs Biomed..

[14]  M. Manjunatha,et al.  Computerised visualisation from images of blood flow through frog mesenteric microvessels with multiple complexities , 2006, Medical and Biological Engineering and Computing.

[15]  Geoffrey G. Zhang,et al.  Use of three‐dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four‐dimensional computed tomography data , 2008, Journal of applied clinical medical physics.

[16]  Geoffrey G. Zhang,et al.  Dose mapping: Validation in 4D dosimetry with measurements and application in radiotherapy follow-up evaluation , 2008, Comput. Methods Programs Biomed..