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  • 1. Sun, Y
    et al.
    Verbeuren, TJ
    Vallez, MO
    Nilsson, Gert
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Sjöberg, Folke
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Anaesthesiology. Östergötlands Läns Landsting, Reconstruction Centre, Department of Plastic Surgery, Hand surgery UHL.
    Volumetric flow mapping for microvascular networks by bimodality imaging with light microscope and laser Doppler imager2004In: Microscopy research and technique (Print), ISSN 1059-910X, E-ISSN 1097-0029, Vol. 65, no 3, p. 130-138Article in journal (Refereed)
    Abstract [en]

    A method was developed to produce a composite image of microvascular networks with grayscales proportional to volumetric flows. Velocities in arterioles and venules were assessed with a high-resolution laser Doppler imager (LDI). The vascular structures were quantified from the micrograph with a computerized vessel detection algorithm. After registering the detected vascular network with the LDI scan, volumetric flows were calculated along the centerlines of the vessels. In vivo data were obtained from the hamster cheek pouch in 6 studies. Flow continuity of the flow map was evaluated by comparing the main flow (Q) with the sum of branch flows (Qs), averaging over the respective vessel segments incident to each bifurcation. The method was reproducible across the 6 studies with the correlation coefficient (r) between Qs and Q ranging from 0.913 to 0.986. In all, over 20,000 flow estimates from 360 vessel segments (24-160 μm in diameter) at 166 bifurcations were analyzed. With flow normalized between 0 and 1, the linear regression yielded: Qs = 1.03 Q + 0.006, r = 0.952, n = 166, P < 0.0005. The bimodality imaging method exploits a large amount of velocity and diameter data, and therefore should be useful for studying heterogeneous flows in the microvasculature. © 2004 Wiley-Liss, Inc.

  • 2.
    Von Tiedemann, M.
    et al.
    Karolinska Institutet, Stockholm, Sweden.
    Fridberger, Anders
    Karolinska Institutet, Stockholm, Sweden.
    Ulfendahl, M.
    Karolinska Institutet, Stockholm, Sweden.
    Boutet de Monvel, J.
    Karolinska Institutet, Stockholm, Sweden.
    Image adaptive point-spread function estimation and deconvolution for in vivo confocal microscopy2006In: Microscopy research and technique (Print), ISSN 1059-910X, E-ISSN 1097-0029, Vol. 69, no 1, p. 10-20Article in journal (Refereed)
    Abstract [en]

    Visualizing deep inside the tissue of a thick biological sample often poses severe constraints on image conditions. Standard restoration techniques (denoising and deconvolution) can then be very useful, allowing one to increase the signal-to-noise ratio and the resolution of the images. In this paper, we consider the problem of obtaining a good determination of the point-spread function (PSF) of a confocal microscope, a prerequisite for applying deconvolution to three-dimensional image stacks acquired with this system. Because of scattering and optical distortion induced by the sample, the PSF has to be acquired anew for each experiment. To tackle this problem, we used a screening approach to estimate the PSF adaptively and automatically from the images. Small PSF-like structures were detected in the images, and a theoretical PSF model reshaped to match the geometric characteristics of these structures. We used numerical experiments to quantify the sensitivity of our detection method, and we demonstrated its usefulness by deconvolving images of the hearing organ acquired in vitro and in vivo.

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