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

Huang, Tzung-Chi; Lin, Wen-Chen; Wu, Chih Chieh; Zhang, Geoffrey; Lin, Kang‐Ping

doi:10.1016/j.mvr.2010.07.007

Cited by 23 publications

(14 citation statements)

References 17 publications

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“…Optical flow method (OFM) developed for motion estimation is applied on the aligned images for blood flow estimation in this study [19]. The spatial accuracy of blood flow estimation calculated by OFM was reported in the previous studies [20–23]. In this study, the OFM algorithm was applied to calculate the velocity of blood flow on two successive images of DSA.…”

Section: Methodsmentioning

confidence: 93%

Quantitative Portal Vein Velocity of Liver Cancer Patients with Transcatheter Arterial Chemoembolization on Angiography

Chang

Lin

et al. 2012

The Scientific World Journal

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Objective. We applied optical flow method (OFM) to quantify relative velocities of blood flow using digital subtraction angiography (DSA) in the vascular analysis of hepatocellular carcinoma (HCC) patients who underwent transarterial chemoembolization (TACE) treatment. Methods. A total of 40 HCC patients treated by TACE were analyzed in this study. DSA imaging with a 12-inch field of view, 1024 × 1024 pixels and 4 frames/second was acquired. OFM developed for motion estimation is applied for blood flow estimation. Two acrylic phantoms were built to validate the method. Results. The relationship between the OFM and Doppler measurements was found linear with R 2 = 0.99 for both straight and curved tube phantoms. Quantitative blood flow distribution images of the portal vein region were presented. After TACE, the minimum, maximum and mean velocities in the portal vein all decreased (P < 0.05). Additionally, the velocity in the portal vein is significantly lower with a higher Child-Pugh score (P < 0.01). Conclusions. The present technique provides add-on quantitative information of flows to DSA and the hemodynamic analysis in relative quantifications of blood flow in portal vein of hepatocellular carcinoma patients using DSA.

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Section: Methodsmentioning

confidence: 93%

Quantitative Portal Vein Velocity of Liver Cancer Patients with Transcatheter Arterial Chemoembolization on Angiography

Chang

Lin

et al. 2012

The Scientific World Journal

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“…To increase the accuracy of the OFM, we added the “Iterative-Amendment Feature” to the original method. This modified optical flow process had been previously validated [19]. A total of 12 regions of interest (ROI) in addition to the ICA, consisting of 3 × 3 pixels, were selected to calculate the average velocity in the AP and lateral views, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…The velocity matrix, which was calculated by the OFM, included the lateral and inferior-superior displacements, which corresponded to each voxel in the images. The spatial accuracy of the blood flow estimation, which was calculated by the OFM, was reported [19]–[20]. We previously applied the OFM to measure the relative velocities of blood flow using angiography and investigated the vascular effects on hepatocellular carcinoma patients who underwent transarterial chemoembolization [21].…”

Section: Methodsmentioning

confidence: 99%

Quantification of Blood Flow in Internal Cerebral Artery by Optical Flow Method on Digital Subtraction Angiography in Comparison with Time-Of-Flight Magnetic Resonance Angiography

et al. 2013

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ObjectiveThis study compared data on the blood flow velocity in the internal carotid artery, which was obtained using the optical flow method (OFM) with digital subtraction angiography (DSA) and the time-of-flight (TOF) technique using magnetic resonance angiography (MRA).Materials and MethodsImages were obtained from 12 cerebrovascular patients who underwent both brain DSA and MRA imaging. The OFM was applied on the DSA images to determine the average blood flow velocity. The calculated results were compared with the values obtained from the TOF-MRA data. A linear fit was performed on the data and Bland-Altman plots were analyzed.ResultsThe blood flow velocity was closely associated with vascular diseases. Color-coding of the OFM measurements were superimposed on to the DSA images, which quantitatively illustrated the relative flow in the vessels. The average blood flow velocity was calculated using OFM and DSA, which demonstrated a high correlation with the MRA measurements in the anterior-posterior (AP) view (R = 0.71). In contrast, the average blood flow velocity was low in the lateral view (R = 0.28). The consistency between the high and low blood velocity in the AP view was better compared to the lateral view. The blood flow velocity distribution in the AP view was statistically closer to the MRA measurement compared to the lateral view.ConclusionsThis study evaluated the correlation of blood flow measured using DSA and TOF-MRA in a small heterogeneous group of patients with cerebrovascular lesions. OFM with DSA imaging reveals hemodynamic information and TOF-MRA.

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“…Previous attempts have been made to apply various motion estimation methods on high-speed microscopic video (1000+ frames/sec) or synthetic image sequences. Huang et al in [2] applied three popular methods, which include crosscorrelation, optical flow, and Hough transform, to a simulated experiment. The results indicate that among these three methods, optical flow produces less error on average.…”

Section: Introductionmentioning

confidence: 99%

Measurement of blood flow velocity forin vivovideo sequences with motion estimation methods

Saber

Glading

Helguera³

2014

SPIE Proceedings

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Measurement of blood flow velocity for in vivo microscopic video is an invasive approach to study microcirculation systems, which has been applied in clinical analysis and physiological study. The video sequences investigated in this paper are recording the microcirculation in a rat brain using a CCD camera with a frame rate of 30 fps. To evaluate the accuracy and feasibility of applying motion estimation methods, we have compared both current optical flow and particle image velocimetry (PIV) techniques using cross-correlation by testing them with simulated vessel images and in vivo microscopic video sequences. The accuracy is evaluated by calculating the mean square root values of the results of these two methods based on ground truth. The limitations of applying both algorithms to our particular video sequences are discussed in terms of noise, the effect of large displacements, and vascular structures. The sources of erroneous motion vectors resulting from utilizing microscopic video with standard frame rate are addressed in this paper. Based on the above, a modified cross-correlation PIV technique called adaptive window cross-correlation (AWCC) is proposed to improve the performance of detecting motions in thinner and slightly complex vascular structures.

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

Cited by 23 publications

References 17 publications

Quantitative Portal Vein Velocity of Liver Cancer Patients with Transcatheter Arterial Chemoembolization on Angiography

Quantitative Portal Vein Velocity of Liver Cancer Patients with Transcatheter Arterial Chemoembolization on Angiography

Quantification of Blood Flow in Internal Cerebral Artery by Optical Flow Method on Digital Subtraction Angiography in Comparison with Time-Of-Flight Magnetic Resonance Angiography

Measurement of blood flow velocity forin vivovideo sequences with motion estimation methods

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