9 March 2011 Deconvolution of dynamic dual photon microscopy images of cerebral microvasculature to assess the hemodynamic status of the brain
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Proceedings Volume 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging; 79650A (2011); doi: 10.1117/12.878741
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States
Abstract
Assessing the hemodynamic status of the brain and its variations in response to stimulations is required to understand the local cerebral circulatory mechanisms. Dynamic contrast enhanced imaging of cerebral microvasculature provides information that can be used in understanding physiology of cerebral diseases. Bolus tracking is used to extract characteristic parameters that quantify local cerebral blood flow. However, post-processing of the data is needed to segment the field of view (FOV) and to perform deconvolution to remove the effects of input bolus profile and the path it travels to reach the imaging window. Finding the arterial input function (AIF) and dealing with the ill-posedness of deconvolution system make this process are the main challenges. We propose using ICA to segment the FOV and to extract a local AIF as well as the venous output function that is required for deconvolution. This also helps to stabilize the system as ICA suppresses noise efficiently. Tikhoniv regularization (with L-curve analysis to find the best regularization parameter) is used to make the system stable. In-vivo dynamic 2PLSM images of a rat brain in two conditions (when the animal is at rest and when it is stimulated) are used in this study. The experimental along with the simulation studies provided promising results that demonstrate the feasibility and importance of performing deconvolution.
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Hatef Mehrabian, Liis Lindvere, Bojana Stefanovic, Anne L. Martel, "Deconvolution of dynamic dual photon microscopy images of cerebral microvasculature to assess the hemodynamic status of the brain", Proc. SPIE 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging, 79650A (9 March 2011); doi: 10.1117/12.878741; https://doi.org/10.1117/12.878741
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KEYWORDS
Arteries

Deconvolution

Veins

Independent component analysis

Brain

Hemodynamics

Image segmentation

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