An Algorithm for Microcirculatory Blood Flow Velocity Measurement Based on Trace Orientation in Spatiotemporal Image_Journal of Biomedical Engineering

Authors：

LUFei ,  ZHAOXingqun

School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China;

Corresponding author：

ZHAOXingqun, Email: ndt@seu.edu.cn

Keywords：

microcirculation; velocity measurement; spatiotemporal image; trace orientation; randomized Hough transformation

DOI：

10.7507/1001-5515.20150080

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

The velocity of blood in vessels is an important indicator that reflects the microcirculatory status. The core of the measurement technology, which is based on spatiotemporal (ST) image, is to map the cell motion trace to the two-dimensional ST image, and transfer the measurement of flow velocity to the detection of trace orientation in ST image. This paper proposes a trace orientation measurement algorithm is based on Randomized Hough Transformation and projection transformation, and it is able to estimate trace orientation and flow velocity in noisy ST images. Experiments showed that the agreement between the results by manual and by the proposed algorithm reached over 90%.

Citation： LUFei, ZHAOXingqun. An Algorithm for Microcirculatory Blood Flow Velocity Measurement Based on Trace Orientation in Spatiotemporal Image. Journal of Biomedical Engineering, 2015, 32(2): 446-450. doi: 10.7507/1001-5515.20150080 Copy

1.	OSPINA-TASCON G, NEVES A P, OCCHIPINTI G A, et al. Effects of fluids on microvascular perfusion in patients with severe sepsis[J]. Intensive Care Med, 2010, 36(6):949-955.
2.	BEZEMER R, BARTELS S A, BAKKER J, et al. Clinical review:Clinical imaging of the sublingual microcirculation in the critically ill--where do we stand?[J]. Critical Care, 2012, 16(3):224.
3.	LEE J Y, JI H S, LEE S J. Micro-PIV measurements of blood flow in extraembryonic blood vessels of chicken embryos[J]. Physiol Meas, 2007, 28(10):1149-1162.
4.	WU C C, ZHANG G, HUANG T C, et al. Red blood cell velocity measurements of complete capillary in finger nail-fold using optical flow estimation[J]. Microvasc Res, 2009, 78(3):319-324.
5.	WATANABE M, MATSUBARA M, SANADA T, et al. High speed digital video capillaroscopy:nailfold capillary shape analysis and red blood cell velocity measurement[J]. J Biomech Sci Eng, 2007, 2(2):81-92.
6.	BEZEMER R, DOBBE J G, BARTELS S A, et al. Rapid automatic assessment of microvascular density in sidestream dark field images[J]. Med Biol Eng Comput, 2011, 49(11):1269-1278.
7.	YOU S, MASSEY M, SHAPIRO N, et al. A novel line detection method in space-time images for microvascular blood flow analysis in sublingual microcirculatory videos[C]//2013 IEEE 10th International Symposium on Biomedical Imaging:From Nano to Macro. San Francisco, CA:2013:7-11.
8.	DING Yihong, PING Xijian, HU Min, et al. Range image segmentation based on randomized Hough transform[J]. Pattern Recognit Lett, 2005, 26(13):2033-2041.
9.	MANI V R S, ARIVAZHAGAN S. Survey of medical image registration[J]. J Biomed Eng, 2013, 1(2):8-25.
10.	皮净锐, 房斌, 王翊, 等.基于Hessian矩阵和GMM-EM算法的肝脏三维血管树提取[J].生物医学工程学杂志, 2013, 30(3):486-492.
11.	陈远, 赵志敏, 刘磊.基于ST图的微循环血细胞自动跟踪与测量技术[J].东南大学学报:自然科学版, 2011, 41(1):72-76.
12.	赵建军, 熊馨, 张磊, 等.基于CLAHE和top-hat变换的手背静脉图像增强算法[J].激光与红外, 2009, 39(2):220-222.
13.	DOBBE J G G, STREEKSTRA G J, ATASEVER B, et al. Measurement of functional microcirculatory geometry and velocity distributions using automated image analysis[J]. Med Biol Eng Comput, 2008, 46(7):659-670.

1. OSPINA-TASCON G, NEVES A P, OCCHIPINTI G A, et al. Effects of fluids on microvascular perfusion in patients with severe sepsis[J]. Intensive Care Med, 2010, 36(6):949-955.
2. BEZEMER R, BARTELS S A, BAKKER J, et al. Clinical review:Clinical imaging of the sublingual microcirculation in the critically ill--where do we stand?[J]. Critical Care, 2012, 16(3):224.
3. LEE J Y, JI H S, LEE S J. Micro-PIV measurements of blood flow in extraembryonic blood vessels of chicken embryos[J]. Physiol Meas, 2007, 28(10):1149-1162.
4. WU C C, ZHANG G, HUANG T C, et al. Red blood cell velocity measurements of complete capillary in finger nail-fold using optical flow estimation[J]. Microvasc Res, 2009, 78(3):319-324.
5. WATANABE M, MATSUBARA M, SANADA T, et al. High speed digital video capillaroscopy:nailfold capillary shape analysis and red blood cell velocity measurement[J]. J Biomech Sci Eng, 2007, 2(2):81-92.
6. BEZEMER R, DOBBE J G, BARTELS S A, et al. Rapid automatic assessment of microvascular density in sidestream dark field images[J]. Med Biol Eng Comput, 2011, 49(11):1269-1278.
7. YOU S, MASSEY M, SHAPIRO N, et al. A novel line detection method in space-time images for microvascular blood flow analysis in sublingual microcirculatory videos[C]//2013 IEEE 10th International Symposium on Biomedical Imaging:From Nano to Macro. San Francisco, CA:2013:7-11.
8. DING Yihong, PING Xijian, HU Min, et al. Range image segmentation based on randomized Hough transform[J]. Pattern Recognit Lett, 2005, 26(13):2033-2041.
9. MANI V R S, ARIVAZHAGAN S. Survey of medical image registration[J]. J Biomed Eng, 2013, 1(2):8-25.
10. 皮净锐, 房斌, 王翊, 等.基于Hessian矩阵和GMM-EM算法的肝脏三维血管树提取[J].生物医学工程学杂志, 2013, 30(3):486-492.
11. 陈远, 赵志敏, 刘磊.基于ST图的微循环血细胞自动跟踪与测量技术[J].东南大学学报:自然科学版, 2011, 41(1):72-76.
12. 赵建军, 熊馨, 张磊, 等.基于CLAHE和top-hat变换的手背静脉图像增强算法[J].激光与红外, 2009, 39(2):220-222.
13. DOBBE J G G, STREEKSTRA G J, ATASEVER B, et al. Measurement of functional microcirculatory geometry and velocity distributions using automated image analysis[J]. Med Biol Eng Comput, 2008, 46(7):659-670.

Journal of Biomedical Engineering

An Algorithm for Microcirculatory Blood Flow Velocity Measurement Based on Trace Orientation in Spatiotemporal Image

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content