Abstract

Laser speckle imaging is a rapidly developing method to study changes of blood velocity in the vascular networks. However, to assess blood flow and vascular responses it is crucial to measure vessel diameter in addition to blood velocity dynamics. We suggest an algorithm that allows for dynamical masking of a vessel position and measurements of it’s diameter from laser speckle images. This approach demonstrates high reliability and stability.

© 2016 Optical Society of America

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References

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  1. Y. Aizu and T. Asakura, “Bio-speckle phenomena and their application to the evaluation of blood flow,” Opt. Laser Technol. 23, 205–219 (1991).
    [Crossref]
  2. D.A. Boas and A.K. Dunn, “Laser speckle contrast imaging in biomedical optics,” J. Biomed. Opt. 15, 011109 (2010).
    [Crossref] [PubMed]
  3. D. Briers, D.D. Duncan, E. Hirst, and S.J. Kirkpatrick, “Laser speckle contrast imaging: theoretical and practical limitations,” J. Biomed. Opt. 18, 066018 (2013).
    [Crossref] [PubMed]
  4. I.V. Fedosov and V.V. Tuchin, “Bioflow Measuring: Laser Doppler and Speckle Techniques,” in Coherent-Domain Optical Methods: Biomedical Diagnostics, Environmental Monitoring and Material Science, 2nd ed. (Springer-Verlag, 2013) pp. 487–564.
    [Crossref]
  5. H. Cheng, Y. Yan, and T.Q. Duong, “Temporal statistical analysis of laser speckle images and its application to retinal blood-flow imaging,” Opt. Express 16, 10214–10219 (2008).
    [Crossref] [PubMed]
  6. C. Ayata, A.K. Dunn, Y. Gursoy-zdemir, Z. Huang, D.A. Boas, and M.A. Moskowitz, “Laser speckle flowmetry for the study of cerebrovascular physiology in normal and ischemic mouse cortex,” J. Cereb. Blood Flow Metab. 24, 744–755 (2004).
    [Crossref] [PubMed]
  7. N.H. Holstein-Rathlou, O.V. Sosnovtseva, A.N. Pavlov, W.A. Cupples, and C.M. Sorensen, “Nephron blood flow dynamics measured by laser speckle contrast imaging,” Am. J Physiol. Renal Physiol 300, F319–F329 (2011).
    [Crossref]
  8. D.D. Postnov, N.-H. Holstein-Rathlou, and O. Sosnovtseva, “Laser speckle imaging of intra organ drug distribution,” Biomed. Opt. Express 6, 5055–5062 (2015).
    [Crossref] [PubMed]
  9. G. Mahe, A. Humeau-Heurtier, S. Durand, G. Leftheriotis, and P. Abraham, “Assessment of skin microvascular function and dysfunction with laser speckle contrast imaging,” Circulation: Cardiovascular Imaging 5, 155–163 (2012).
    [PubMed]
  10. D. Chen, J. Ren, Y. Wang, H. Zhao, B. Li, and Y. Gu, “Relationship between the blood perfusion values determined by laser speckle imaging and laser Doppler imaging in normal skin and port wine stains,” Photodiagnosis Photodynamic Therapy 13, 1–9 (2016).
    [Crossref]
  11. A.J. Strong, E.L. Bezzina, P.J. Anderson, M.G. Boutelle, S.E. Hopwood, and A.K. Dunn, “Evaluation of laser speckle flowmetry for imaging cortical perfusion in experimental stroke studies: quantitation of perfusion and detection of peri-infarct depolarisations,” J. Cereb. Blood Flow Metab. 26, 645–653 (2006).
    [Crossref]
  12. H. Nilsson and C. Aalkjaer, “Vasomotion: mechanisms and physiological importance,” Molecular Interventions 3, 79 (2003).
    [Crossref]
  13. D.D. Postnov, O. Sosnovtseva, and V.V. Tuchin, “Improved detectability of microcirculatory dynamics by laser speckle flowmetry,” J. Biophoton. 8, 790–794 (2015).
    [Crossref]
  14. Q. Liu, Y. Li, H. Lu, and S. Tong, “Real-time high resolution laser speckle imaging of cerebral vascular changes in a rodent photothrombosis model,” Biomed. Opt. Express 5, 1483–1493 (2014).
    [Crossref] [PubMed]
  15. S.S. Kazmi, E. Faraji, M.A. Davis, Y.Y. Huang, X.J. Zhang, and A.K. Dunn, “Flux or speed? Examining speckle contrast imaging of vascular flows,” Biomed. Opt. Express 6, 2588–2608 (2015).
    [Crossref] [PubMed]
  16. A.Y. Neganova, D.D. Postnov, J.C. Brings-Jacobsen, and O Sosnovtseva, “Laser speckle analysis of retinal vascular dynamics,” Biomed. Opt. Express 7, 1375–1384 (2016).
    [Crossref]

2016 (2)

D. Chen, J. Ren, Y. Wang, H. Zhao, B. Li, and Y. Gu, “Relationship between the blood perfusion values determined by laser speckle imaging and laser Doppler imaging in normal skin and port wine stains,” Photodiagnosis Photodynamic Therapy 13, 1–9 (2016).
[Crossref]

A.Y. Neganova, D.D. Postnov, J.C. Brings-Jacobsen, and O Sosnovtseva, “Laser speckle analysis of retinal vascular dynamics,” Biomed. Opt. Express 7, 1375–1384 (2016).
[Crossref]

2015 (3)

2014 (1)

2013 (1)

D. Briers, D.D. Duncan, E. Hirst, and S.J. Kirkpatrick, “Laser speckle contrast imaging: theoretical and practical limitations,” J. Biomed. Opt. 18, 066018 (2013).
[Crossref] [PubMed]

2012 (1)

G. Mahe, A. Humeau-Heurtier, S. Durand, G. Leftheriotis, and P. Abraham, “Assessment of skin microvascular function and dysfunction with laser speckle contrast imaging,” Circulation: Cardiovascular Imaging 5, 155–163 (2012).
[PubMed]

2011 (1)

N.H. Holstein-Rathlou, O.V. Sosnovtseva, A.N. Pavlov, W.A. Cupples, and C.M. Sorensen, “Nephron blood flow dynamics measured by laser speckle contrast imaging,” Am. J Physiol. Renal Physiol 300, F319–F329 (2011).
[Crossref]

2010 (1)

D.A. Boas and A.K. Dunn, “Laser speckle contrast imaging in biomedical optics,” J. Biomed. Opt. 15, 011109 (2010).
[Crossref] [PubMed]

2008 (1)

2006 (1)

A.J. Strong, E.L. Bezzina, P.J. Anderson, M.G. Boutelle, S.E. Hopwood, and A.K. Dunn, “Evaluation of laser speckle flowmetry for imaging cortical perfusion in experimental stroke studies: quantitation of perfusion and detection of peri-infarct depolarisations,” J. Cereb. Blood Flow Metab. 26, 645–653 (2006).
[Crossref]

2004 (1)

C. Ayata, A.K. Dunn, Y. Gursoy-zdemir, Z. Huang, D.A. Boas, and M.A. Moskowitz, “Laser speckle flowmetry for the study of cerebrovascular physiology in normal and ischemic mouse cortex,” J. Cereb. Blood Flow Metab. 24, 744–755 (2004).
[Crossref] [PubMed]

2003 (1)

H. Nilsson and C. Aalkjaer, “Vasomotion: mechanisms and physiological importance,” Molecular Interventions 3, 79 (2003).
[Crossref]

1991 (1)

Y. Aizu and T. Asakura, “Bio-speckle phenomena and their application to the evaluation of blood flow,” Opt. Laser Technol. 23, 205–219 (1991).
[Crossref]

Aalkjaer, C.

H. Nilsson and C. Aalkjaer, “Vasomotion: mechanisms and physiological importance,” Molecular Interventions 3, 79 (2003).
[Crossref]

Abraham, P.

G. Mahe, A. Humeau-Heurtier, S. Durand, G. Leftheriotis, and P. Abraham, “Assessment of skin microvascular function and dysfunction with laser speckle contrast imaging,” Circulation: Cardiovascular Imaging 5, 155–163 (2012).
[PubMed]

Aizu, Y.

Y. Aizu and T. Asakura, “Bio-speckle phenomena and their application to the evaluation of blood flow,” Opt. Laser Technol. 23, 205–219 (1991).
[Crossref]

Anderson, P.J.

A.J. Strong, E.L. Bezzina, P.J. Anderson, M.G. Boutelle, S.E. Hopwood, and A.K. Dunn, “Evaluation of laser speckle flowmetry for imaging cortical perfusion in experimental stroke studies: quantitation of perfusion and detection of peri-infarct depolarisations,” J. Cereb. Blood Flow Metab. 26, 645–653 (2006).
[Crossref]

Asakura, T.

Y. Aizu and T. Asakura, “Bio-speckle phenomena and their application to the evaluation of blood flow,” Opt. Laser Technol. 23, 205–219 (1991).
[Crossref]

Ayata, C.

C. Ayata, A.K. Dunn, Y. Gursoy-zdemir, Z. Huang, D.A. Boas, and M.A. Moskowitz, “Laser speckle flowmetry for the study of cerebrovascular physiology in normal and ischemic mouse cortex,” J. Cereb. Blood Flow Metab. 24, 744–755 (2004).
[Crossref] [PubMed]

Bezzina, E.L.

A.J. Strong, E.L. Bezzina, P.J. Anderson, M.G. Boutelle, S.E. Hopwood, and A.K. Dunn, “Evaluation of laser speckle flowmetry for imaging cortical perfusion in experimental stroke studies: quantitation of perfusion and detection of peri-infarct depolarisations,” J. Cereb. Blood Flow Metab. 26, 645–653 (2006).
[Crossref]

Boas, D.A.

D.A. Boas and A.K. Dunn, “Laser speckle contrast imaging in biomedical optics,” J. Biomed. Opt. 15, 011109 (2010).
[Crossref] [PubMed]

C. Ayata, A.K. Dunn, Y. Gursoy-zdemir, Z. Huang, D.A. Boas, and M.A. Moskowitz, “Laser speckle flowmetry for the study of cerebrovascular physiology in normal and ischemic mouse cortex,” J. Cereb. Blood Flow Metab. 24, 744–755 (2004).
[Crossref] [PubMed]

Boutelle, M.G.

A.J. Strong, E.L. Bezzina, P.J. Anderson, M.G. Boutelle, S.E. Hopwood, and A.K. Dunn, “Evaluation of laser speckle flowmetry for imaging cortical perfusion in experimental stroke studies: quantitation of perfusion and detection of peri-infarct depolarisations,” J. Cereb. Blood Flow Metab. 26, 645–653 (2006).
[Crossref]

Briers, D.

D. Briers, D.D. Duncan, E. Hirst, and S.J. Kirkpatrick, “Laser speckle contrast imaging: theoretical and practical limitations,” J. Biomed. Opt. 18, 066018 (2013).
[Crossref] [PubMed]

Brings-Jacobsen, J.C.

Chen, D.

D. Chen, J. Ren, Y. Wang, H. Zhao, B. Li, and Y. Gu, “Relationship between the blood perfusion values determined by laser speckle imaging and laser Doppler imaging in normal skin and port wine stains,” Photodiagnosis Photodynamic Therapy 13, 1–9 (2016).
[Crossref]

Cheng, H.

Cupples, W.A.

N.H. Holstein-Rathlou, O.V. Sosnovtseva, A.N. Pavlov, W.A. Cupples, and C.M. Sorensen, “Nephron blood flow dynamics measured by laser speckle contrast imaging,” Am. J Physiol. Renal Physiol 300, F319–F329 (2011).
[Crossref]

Davis, M.A.

Duncan, D.D.

D. Briers, D.D. Duncan, E. Hirst, and S.J. Kirkpatrick, “Laser speckle contrast imaging: theoretical and practical limitations,” J. Biomed. Opt. 18, 066018 (2013).
[Crossref] [PubMed]

Dunn, A.K.

S.S. Kazmi, E. Faraji, M.A. Davis, Y.Y. Huang, X.J. Zhang, and A.K. Dunn, “Flux or speed? Examining speckle contrast imaging of vascular flows,” Biomed. Opt. Express 6, 2588–2608 (2015).
[Crossref] [PubMed]

D.A. Boas and A.K. Dunn, “Laser speckle contrast imaging in biomedical optics,” J. Biomed. Opt. 15, 011109 (2010).
[Crossref] [PubMed]

A.J. Strong, E.L. Bezzina, P.J. Anderson, M.G. Boutelle, S.E. Hopwood, and A.K. Dunn, “Evaluation of laser speckle flowmetry for imaging cortical perfusion in experimental stroke studies: quantitation of perfusion and detection of peri-infarct depolarisations,” J. Cereb. Blood Flow Metab. 26, 645–653 (2006).
[Crossref]

C. Ayata, A.K. Dunn, Y. Gursoy-zdemir, Z. Huang, D.A. Boas, and M.A. Moskowitz, “Laser speckle flowmetry for the study of cerebrovascular physiology in normal and ischemic mouse cortex,” J. Cereb. Blood Flow Metab. 24, 744–755 (2004).
[Crossref] [PubMed]

Duong, T.Q.

Durand, S.

G. Mahe, A. Humeau-Heurtier, S. Durand, G. Leftheriotis, and P. Abraham, “Assessment of skin microvascular function and dysfunction with laser speckle contrast imaging,” Circulation: Cardiovascular Imaging 5, 155–163 (2012).
[PubMed]

Faraji, E.

Fedosov, I.V.

I.V. Fedosov and V.V. Tuchin, “Bioflow Measuring: Laser Doppler and Speckle Techniques,” in Coherent-Domain Optical Methods: Biomedical Diagnostics, Environmental Monitoring and Material Science, 2nd ed. (Springer-Verlag, 2013) pp. 487–564.
[Crossref]

Gu, Y.

D. Chen, J. Ren, Y. Wang, H. Zhao, B. Li, and Y. Gu, “Relationship between the blood perfusion values determined by laser speckle imaging and laser Doppler imaging in normal skin and port wine stains,” Photodiagnosis Photodynamic Therapy 13, 1–9 (2016).
[Crossref]

Gursoy-zdemir, Y.

C. Ayata, A.K. Dunn, Y. Gursoy-zdemir, Z. Huang, D.A. Boas, and M.A. Moskowitz, “Laser speckle flowmetry for the study of cerebrovascular physiology in normal and ischemic mouse cortex,” J. Cereb. Blood Flow Metab. 24, 744–755 (2004).
[Crossref] [PubMed]

Hirst, E.

D. Briers, D.D. Duncan, E. Hirst, and S.J. Kirkpatrick, “Laser speckle contrast imaging: theoretical and practical limitations,” J. Biomed. Opt. 18, 066018 (2013).
[Crossref] [PubMed]

Holstein-Rathlou, N.H.

N.H. Holstein-Rathlou, O.V. Sosnovtseva, A.N. Pavlov, W.A. Cupples, and C.M. Sorensen, “Nephron blood flow dynamics measured by laser speckle contrast imaging,” Am. J Physiol. Renal Physiol 300, F319–F329 (2011).
[Crossref]

Holstein-Rathlou, N.-H.

Hopwood, S.E.

A.J. Strong, E.L. Bezzina, P.J. Anderson, M.G. Boutelle, S.E. Hopwood, and A.K. Dunn, “Evaluation of laser speckle flowmetry for imaging cortical perfusion in experimental stroke studies: quantitation of perfusion and detection of peri-infarct depolarisations,” J. Cereb. Blood Flow Metab. 26, 645–653 (2006).
[Crossref]

Huang, Y.Y.

Huang, Z.

C. Ayata, A.K. Dunn, Y. Gursoy-zdemir, Z. Huang, D.A. Boas, and M.A. Moskowitz, “Laser speckle flowmetry for the study of cerebrovascular physiology in normal and ischemic mouse cortex,” J. Cereb. Blood Flow Metab. 24, 744–755 (2004).
[Crossref] [PubMed]

Humeau-Heurtier, A.

G. Mahe, A. Humeau-Heurtier, S. Durand, G. Leftheriotis, and P. Abraham, “Assessment of skin microvascular function and dysfunction with laser speckle contrast imaging,” Circulation: Cardiovascular Imaging 5, 155–163 (2012).
[PubMed]

Kazmi, S.S.

Kirkpatrick, S.J.

D. Briers, D.D. Duncan, E. Hirst, and S.J. Kirkpatrick, “Laser speckle contrast imaging: theoretical and practical limitations,” J. Biomed. Opt. 18, 066018 (2013).
[Crossref] [PubMed]

Leftheriotis, G.

G. Mahe, A. Humeau-Heurtier, S. Durand, G. Leftheriotis, and P. Abraham, “Assessment of skin microvascular function and dysfunction with laser speckle contrast imaging,” Circulation: Cardiovascular Imaging 5, 155–163 (2012).
[PubMed]

Li, B.

D. Chen, J. Ren, Y. Wang, H. Zhao, B. Li, and Y. Gu, “Relationship between the blood perfusion values determined by laser speckle imaging and laser Doppler imaging in normal skin and port wine stains,” Photodiagnosis Photodynamic Therapy 13, 1–9 (2016).
[Crossref]

Li, Y.

Liu, Q.

Lu, H.

Mahe, G.

G. Mahe, A. Humeau-Heurtier, S. Durand, G. Leftheriotis, and P. Abraham, “Assessment of skin microvascular function and dysfunction with laser speckle contrast imaging,” Circulation: Cardiovascular Imaging 5, 155–163 (2012).
[PubMed]

Moskowitz, M.A.

C. Ayata, A.K. Dunn, Y. Gursoy-zdemir, Z. Huang, D.A. Boas, and M.A. Moskowitz, “Laser speckle flowmetry for the study of cerebrovascular physiology in normal and ischemic mouse cortex,” J. Cereb. Blood Flow Metab. 24, 744–755 (2004).
[Crossref] [PubMed]

Neganova, A.Y.

Nilsson, H.

H. Nilsson and C. Aalkjaer, “Vasomotion: mechanisms and physiological importance,” Molecular Interventions 3, 79 (2003).
[Crossref]

Pavlov, A.N.

N.H. Holstein-Rathlou, O.V. Sosnovtseva, A.N. Pavlov, W.A. Cupples, and C.M. Sorensen, “Nephron blood flow dynamics measured by laser speckle contrast imaging,” Am. J Physiol. Renal Physiol 300, F319–F329 (2011).
[Crossref]

Postnov, D.D.

Ren, J.

D. Chen, J. Ren, Y. Wang, H. Zhao, B. Li, and Y. Gu, “Relationship between the blood perfusion values determined by laser speckle imaging and laser Doppler imaging in normal skin and port wine stains,” Photodiagnosis Photodynamic Therapy 13, 1–9 (2016).
[Crossref]

Sorensen, C.M.

N.H. Holstein-Rathlou, O.V. Sosnovtseva, A.N. Pavlov, W.A. Cupples, and C.M. Sorensen, “Nephron blood flow dynamics measured by laser speckle contrast imaging,” Am. J Physiol. Renal Physiol 300, F319–F329 (2011).
[Crossref]

Sosnovtseva, O

Sosnovtseva, O.

D.D. Postnov, N.-H. Holstein-Rathlou, and O. Sosnovtseva, “Laser speckle imaging of intra organ drug distribution,” Biomed. Opt. Express 6, 5055–5062 (2015).
[Crossref] [PubMed]

D.D. Postnov, O. Sosnovtseva, and V.V. Tuchin, “Improved detectability of microcirculatory dynamics by laser speckle flowmetry,” J. Biophoton. 8, 790–794 (2015).
[Crossref]

Sosnovtseva, O.V.

N.H. Holstein-Rathlou, O.V. Sosnovtseva, A.N. Pavlov, W.A. Cupples, and C.M. Sorensen, “Nephron blood flow dynamics measured by laser speckle contrast imaging,” Am. J Physiol. Renal Physiol 300, F319–F329 (2011).
[Crossref]

Strong, A.J.

A.J. Strong, E.L. Bezzina, P.J. Anderson, M.G. Boutelle, S.E. Hopwood, and A.K. Dunn, “Evaluation of laser speckle flowmetry for imaging cortical perfusion in experimental stroke studies: quantitation of perfusion and detection of peri-infarct depolarisations,” J. Cereb. Blood Flow Metab. 26, 645–653 (2006).
[Crossref]

Tong, S.

Tuchin, V.V.

D.D. Postnov, O. Sosnovtseva, and V.V. Tuchin, “Improved detectability of microcirculatory dynamics by laser speckle flowmetry,” J. Biophoton. 8, 790–794 (2015).
[Crossref]

I.V. Fedosov and V.V. Tuchin, “Bioflow Measuring: Laser Doppler and Speckle Techniques,” in Coherent-Domain Optical Methods: Biomedical Diagnostics, Environmental Monitoring and Material Science, 2nd ed. (Springer-Verlag, 2013) pp. 487–564.
[Crossref]

Wang, Y.

D. Chen, J. Ren, Y. Wang, H. Zhao, B. Li, and Y. Gu, “Relationship between the blood perfusion values determined by laser speckle imaging and laser Doppler imaging in normal skin and port wine stains,” Photodiagnosis Photodynamic Therapy 13, 1–9 (2016).
[Crossref]

Yan, Y.

Zhang, X.J.

Zhao, H.

D. Chen, J. Ren, Y. Wang, H. Zhao, B. Li, and Y. Gu, “Relationship between the blood perfusion values determined by laser speckle imaging and laser Doppler imaging in normal skin and port wine stains,” Photodiagnosis Photodynamic Therapy 13, 1–9 (2016).
[Crossref]

Am. J Physiol. Renal Physiol (1)

N.H. Holstein-Rathlou, O.V. Sosnovtseva, A.N. Pavlov, W.A. Cupples, and C.M. Sorensen, “Nephron blood flow dynamics measured by laser speckle contrast imaging,” Am. J Physiol. Renal Physiol 300, F319–F329 (2011).
[Crossref]

Biomed. Opt. Express (4)

Circulation: Cardiovascular Imaging (1)

G. Mahe, A. Humeau-Heurtier, S. Durand, G. Leftheriotis, and P. Abraham, “Assessment of skin microvascular function and dysfunction with laser speckle contrast imaging,” Circulation: Cardiovascular Imaging 5, 155–163 (2012).
[PubMed]

J. Biomed. Opt. (2)

D.A. Boas and A.K. Dunn, “Laser speckle contrast imaging in biomedical optics,” J. Biomed. Opt. 15, 011109 (2010).
[Crossref] [PubMed]

D. Briers, D.D. Duncan, E. Hirst, and S.J. Kirkpatrick, “Laser speckle contrast imaging: theoretical and practical limitations,” J. Biomed. Opt. 18, 066018 (2013).
[Crossref] [PubMed]

J. Biophoton. (1)

D.D. Postnov, O. Sosnovtseva, and V.V. Tuchin, “Improved detectability of microcirculatory dynamics by laser speckle flowmetry,” J. Biophoton. 8, 790–794 (2015).
[Crossref]

J. Cereb. Blood Flow Metab. (2)

C. Ayata, A.K. Dunn, Y. Gursoy-zdemir, Z. Huang, D.A. Boas, and M.A. Moskowitz, “Laser speckle flowmetry for the study of cerebrovascular physiology in normal and ischemic mouse cortex,” J. Cereb. Blood Flow Metab. 24, 744–755 (2004).
[Crossref] [PubMed]

A.J. Strong, E.L. Bezzina, P.J. Anderson, M.G. Boutelle, S.E. Hopwood, and A.K. Dunn, “Evaluation of laser speckle flowmetry for imaging cortical perfusion in experimental stroke studies: quantitation of perfusion and detection of peri-infarct depolarisations,” J. Cereb. Blood Flow Metab. 26, 645–653 (2006).
[Crossref]

Molecular Interventions (1)

H. Nilsson and C. Aalkjaer, “Vasomotion: mechanisms and physiological importance,” Molecular Interventions 3, 79 (2003).
[Crossref]

Opt. Express (1)

Opt. Laser Technol. (1)

Y. Aizu and T. Asakura, “Bio-speckle phenomena and their application to the evaluation of blood flow,” Opt. Laser Technol. 23, 205–219 (1991).
[Crossref]

Photodiagnosis Photodynamic Therapy (1)

D. Chen, J. Ren, Y. Wang, H. Zhao, B. Li, and Y. Gu, “Relationship between the blood perfusion values determined by laser speckle imaging and laser Doppler imaging in normal skin and port wine stains,” Photodiagnosis Photodynamic Therapy 13, 1–9 (2016).
[Crossref]

Other (1)

I.V. Fedosov and V.V. Tuchin, “Bioflow Measuring: Laser Doppler and Speckle Techniques,” in Coherent-Domain Optical Methods: Biomedical Diagnostics, Environmental Monitoring and Material Science, 2nd ed. (Springer-Verlag, 2013) pp. 487–564.
[Crossref]

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Figures (5)

Fig. 1
Fig. 1 Schematic presentation of the experiment setup: (a) Imaging of mesenterium arteries and (b) laser speckle imaging of vascular network in mouse cortex. Both experiments are done in vivo on anesthetized animals.
Fig. 2
Fig. 2 Main steps of the algorithm for diameter estimation. The top panel represents a frame of non-smoothed laser speckle data and corresponding SV values along vertical (green) and horizontal (blue) scan lines. Step I: Rough estimation of the vessel location and geometry from smoothed data. Notice that the horizontal scan provides better visualization of the vessel geometry. Step II: Detection of the center line (red) that always belongs to the vessel, creation of the vessel profile obtained as an average of speckle values over all horizontal scan lines of the frame and centered along the center line coordinates. Step III: Estimation of the vessel boundary (black) by calculating a relative SV drop from the center line and the minimum of the second order gradient.
Fig. 3
Fig. 3 Left panel: Microphotography of a vessel. Red color indicates the outer diameter and green color marks the inner diameter. Right panel: Relative error of the diameter estimation calculated from (2) after the step I (dashed curve) and for the step III (solid curve).
Fig. 4
Fig. 4 Estimation of speckle value SV through the average over the regions of interest (left panels) and through dynamical masking approach (right panels). (a) SV frame averaged over 110 s. Regions R1 and R2 are chosen for the calculation of SV; (b) SV dynamics in R1 (green) and R2 (blue). Notice that dynamics depends significantly on the selected regions of interest; (c) Mask averaged over time. The higher values indicate that the vessel is detected at the corresponding pixels for longer time; (d) SV measured from the central line along the vessel (gray), diameter D calculated according to our algorithm (magenta) and flow dynamics F estimated from SV measurements and calculated diameter. All curves are normalized by the baseline value recorded for the first 10 s. Notice that SV dynamics calculated from the regions R1 and R2 does not correspond to the dynamics measured via dynamical masking. This difference is caused by changing diameter.
Fig. 5
Fig. 5 Diameter changes in the mouse cortex vascular network during control measurements (a), vessel contraction at the beginning of NaCl perfusion (b), and vessel relaxation during continuous NaCl perfusion (c). The bottom panel shows the enlarged region marked on (a) for all three images on the top panel. Diameter of the vessels is coded by color. Color-coded diameter is mapped on the mask of vascular network. We used the same mask in (a), (b), and (c) that was calculated as an average mask over all frames.

Tables (1)

Tables Icon

Table 1 Algorithm description.

Equations (3)

Equations on this page are rendered with MathJax. Learn more.

SV = I 2 ¯ / σ 2 ,
Error = | D v D c D c | × 100 % ,
F ( t ) = D ( t ) 2 × SV ( t ) ,

Metrics