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.”

References

References
1.
Boersma
,
E.
,
Mercado
,
N.
,
Poldermans
,
D.
,
Gardien
,
M.
,
Vos
,
J.
, and
Simoons
,
M. L.
,
2003
, “
Acute Myocardial Infarction
,”
Lancet
,
361
(
9360
), pp.
847
858
.
2.
Brisman
,
J. L.
,
Song
,
J. K.
, and
Newell
,
D. W.
,
2006
, “
Cerebral Aneurysms
,”
N. Engl. J. Med.
,
355
(
9
), pp.
928
939
.
3.
Fouras
,
A.
,
Kitchen
,
M. J.
,
Dubsky
,
S.
,
Lewis
,
R. A.
,
Hooper
,
S. B.
, and
Hourigan
,
K.
,
2009
, “
The Past, Present, and Future of X-Ray Technology for In Vivo Imaging of Function and Form
,”
J. Appl. Phys.
,
105
(
10
), p.
102009
.
4.
Malek
,
A. M.
,
Alper
,
S. L.
, and
Izumo
,
S.
,
1999
, “
Hemodynamic Shear Stress and Its Role in Atherosclerosis
,”
JAMA
,
282
(
21
), pp.
2035
2042
.
5.
Jou
,
L. D.
,
Lee
,
D. H.
,
Morsi
,
H.
, and
Mawad
,
M. E.
,
2008
, “
Wall Shear Stress on Ruptured and Unruptured Intracranial Aneurysms at the Internal Carotid Artery
,”
AJNR Am. J. Neuroradiology
,
29
(
9
), pp.
1761
1767
.
6.
Xiang
,
J.
,
Natarajan
,
S. K.
,
Tremmel
,
M.
,
Ma
,
D.
,
Mocco
,
J.
,
Hopkins
,
L. N.
,
Levy
,
E. I.
, and
Meng
,
H.
,
2011
, “
Hemodynamic-Morphologic Discriminants for Intracranial Aneurysm Rupture
,”
Stroke
,
42
(
1
), pp.
144
152
.
7.
Pereira
,
V. M.
,
Ouared
,
R.
,
Brian
,
O.
,
Bonnefous
,
O.
,
Satwiaski
,
J.
,
Aerts
,
H.
,
Ruijters
,
D.
,
van Nijnatten
,
F.
,
Perren
,
F.
,
Bijlenga
,
P.
,
Schaller
,
K.
, and
Lovblad
,
K. O.
,
2014
, “
Quantification of Internal Carotid Artery Flow With Digital Subtraction Angiography: Validation of An Optical Flow Approach With Doppler Ultrasound
,”
AJNR Am. J. Neuroradiology
,
35
(
1
), pp.
156
163
.
8.
Shpilfoygel
,
S.
,
Close
,
R.
,
Valentino
,
D.
, and
Duckwiler
,
G.
,
2000
, “
X-Ray Videodensitometric Methods for Blood Flow and Velocity Measurement: A Critical Review of Literature
,”
Med. Phys.
,
27
(
9
), pp.
2008
2023
.
9.
Horn
,
B. K.
, and
Schunck
,
B. G.
,
1981
, “
Determining Optical Flow
,”
Artif. Intell.
,
17
(1–3), pp.
185
204
.
10.
Corpetti
,
T.
,
Memin
,
E.
, and
Perez
,
P.
,
2002
, “
Dense Estimation of Fluid Flows
,”
IEEE Trans. Pattern Anal. Mach. Intell.
,
24
(
3
), pp.
365
380
.
11.
Corpetti
,
T.
,
Heitz
,
D.
,
Arroyo
,
G.
,
Memin
,
E.
, and
Santa-Cruz
,
A.
,
2006
, “
Fluid Experimental Flow Estimation Based on an Optical-Flow Scheme
,”
Exp. Fluids
,
40
(
1
), pp.
80
97
.
12.
Ruhnau
,
P.
,
Kohlberger
,
T.
,
Schnorr
,
C.
, and
Nobach
,
H.
,
2005
, “
Variational Optical Flow Estimation for Particle Image Velocimetry
,”
Exp. Fluids
,
38
(
21
), pp.
21
32
.
13.
Yuan
,
J.
,
Schnorr
,
C.
, and
Memin
,
E.
,
2007
, “
Discrete Orthogonal Decomposition and Variation Fluid Flow Estimation
,”
J. Math. Imaging Vision
,
28
(
1
), pp.
67
80
.
14.
Sarry
,
L.
,
Boire
,
J. Y.
,
Zanca
,
M.
,
Lusson
,
J. R.
, and
Cassagnes
,
J.
,
1997
, “
Assessment of Stenosis Severity Using a Novel Method to Estimate Spatial and Temporal Variations of Blood Flow Velocity in Biplane Coronarography
,”
Phys. Med. Biol.
,
42
(
8
), pp.
1549
1564
.
15.
Rhode
,
K.
,
Lambrou
,
T.
,
Hawkes
,
D.
, and
Seifalian
,
A.
,
2005
, “
Novel Approaches to the Measurement of Arterial Blood Flow From Dynamic Digital X-Ray Images
,”
IEEE Trans. Med. Imaging
,
24
(
4
), pp.
500
513
.
16.
Bonnefous
,
O.
,
Pereira
,
V.
,
Ouared
,
R.
,
Rrina
,
O.
,
Aerts
,
H.
,
Hermans
,
R.
,
Nijnatten
,
F.
,
Stawiaski
,
J.
, and
Ruijters
,
D.
,
2012
, “
Quantification of Arterial Flow Using Digital Subtraction Angiography
,”
Med. Phys.
,
39
(
10
), pp.
6264
6275
.
17.
Brina
,
O.
,
Ouared
,
R.
,
Bonnefous
,
O.
,
van Nijnatten
,
F.
,
Bouillot
,
P.
,
Bijlenga
,
P.
,
Schaller
,
K.
,
Lovblad
,
K.
,
Grunhagen
,
T.
,
Ruijters
,
D.
, and
Pereira
,
V.
,
2014
, “
Intra-Aneurysmal Flow Patterns: Illustrative Comparison Among Digital Subtraction Angiography, Optical Flow, and Computational Fluid Dynamics
,”
AJNR Am. J. Neuroradiology
,
35
(
12
), pp.
2348
2353
.
18.
Huang
,
T.
,
Wu
,
T.
,
Lin
,
Y.
,
Guo
,
W.
,
Huang
,
W.
, and
Lin
,
C.
,
2013
, “
Quantitative Flow Measurement by Digital Subtraction Angiography in Cerebral Carotid Stenosis Using Optical Flow Method
,”
J. X-Ray Sci. Technol.
,
21
(
2
), pp.
227
235
.
19.
Pereira
,
V. M.
,
Bonnefous
,
O.
,
Ouared
,
R.
,
Brina
,
O.
,
Stawiaski
,
J.
,
Aerts
,
H.
,
Ruijters
,
D.
,
Narata
,
A.
,
Bijlenga
,
P.
,
Schaller
,
K.
, and
Lovblad
,
K.
,
2013
, “
A DSA-Based Method Using Contrast-Motion Estimation for the Assessment of the Intra-Aneurysmal Flow Changes Induced by Flow-Diverter Stents
,”
AJNR Am. J. Neuroradiology
,
34
(
4
), pp.
808
815
.
20.
Liu
,
T.
, and
Shen
,
L.
,
2008
, “
Fluid Flow and Optical Flow
,”
J. Fluid Mech.
,
614
, pp.
253
291
.
21.
Liu
,
T.
,
Merat
,
A.
,
Makhmalbaf
,
M.
,
Fajardo
,
C.
, and
Merati
,
P.
,
2015
, “
Comparison Between Optical Flow and Cross-Correlation Methods for Extraction of Velocity Fields From Particle Images
,”
Exp. Fluids
,
56
(
8
), p.
166
.
22.
Park
,
H.
,
Yeom
,
E.
, and
Lee
,
S. J.
,
2016
, “
X-Ray PIV Measurement of Blood Flow in Deep Vessels of a Rat: An In Vivo Feasibility Study
,”
Sci. Rep.
,
6
(
1
), p.
19194
.
23.
Okamoto
,
K.
,
Nishio
,
S.
,
Saga
,
T.
, and
Kobayashi
,
T.
,
2000
, “
Standard Images for Particle-Image Velocimetry
,”
Meas. Sci. Technol.
,
11
(
6
), pp.
685
691
.
24.
Yang
,
Z.
,
Yu
,
H.
,
Huang
,
P. G.
,
Schwieterman
,
R.
, and
Ludwig
,
B.
,
2015
, “
Computational Fluid Dynamics Simulation of Intracranial Aneurysms—Comparing Size and Shape
,”
J. Coastal Life Med.
,
3
(
3
), pp.
245
252
.
25.
Meng
,
H.
,
Tutino
,
V. M.
,
Xiang
,
J.
, and
Siddiqui
,
A.
,
2014
, “
High WSS or Low WSS? Complex Interactions of Hemodynamics With Intracranial Aneurysm Initiation, Growth, and Rupture: Toward a Unifying Hypothesis
,”
AJNR Am. J. Neuroradiology
,
35
(
7
), pp.
1254
1262
.
26.
Vennemann
,
P.
,
Lindken
,
R.
, and
Westerweel
,
J.
,
2007
, “
In Vivo Whole-Field Blood Velocity Measurement Techniques
,”
Exp. Fluids
,
42
(
4
), pp.
495
511
.
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