UZH-Logo

Maintenance Infos

Dynamic laser speckle imaging of cerebral blood flow


Zakharov, P; Völker, A C; Wyss, M T; Haiss, F; Calcinaghi, N; Zunzunegui, C; Buck, A; Scheffold, F; Weber, B (2009). Dynamic laser speckle imaging of cerebral blood flow. Optics Express, 17(16):13904-139017.

Abstract

Laser speckle imaging (LSI) based on the speckle contrast analysis is a simple and robust technique for imaging of heterogeneous dynamics. LSI finds frequent application for dynamical mapping of cerebral blood flow, as it features high spatial and temporal resolution. However, the quantitative interpretation of the acquired data is not straightforward for the common case of a speckle field formed by both by moving and localized scatterers such as blood cells and bone or tissue. Here we present a novel processing scheme, we call dynamic laser speckle imaging (dLSI), that can be used to correctly extract the temporal correlation parameters from the speckle contrast measured in the presence of a static or slow-evolving background. The static light contribution is derived from the measurements by cross-correlating sequential speckle images. In-vivo speckle imaging experiments performed in the rodent brain demonstrate that dLSI leads to improved results. The cerebral hemodynamic response observed through the thinned and intact skull are more pronounced in the dLSI images as compared to the standard speckle contrast analysis. The proposed method also yields benefits with respect to the quality of the speckle images by suppressing contributions of non-uniformly distributed specular reflections.

Laser speckle imaging (LSI) based on the speckle contrast analysis is a simple and robust technique for imaging of heterogeneous dynamics. LSI finds frequent application for dynamical mapping of cerebral blood flow, as it features high spatial and temporal resolution. However, the quantitative interpretation of the acquired data is not straightforward for the common case of a speckle field formed by both by moving and localized scatterers such as blood cells and bone or tissue. Here we present a novel processing scheme, we call dynamic laser speckle imaging (dLSI), that can be used to correctly extract the temporal correlation parameters from the speckle contrast measured in the presence of a static or slow-evolving background. The static light contribution is derived from the measurements by cross-correlating sequential speckle images. In-vivo speckle imaging experiments performed in the rodent brain demonstrate that dLSI leads to improved results. The cerebral hemodynamic response observed through the thinned and intact skull are more pronounced in the dLSI images as compared to the standard speckle contrast analysis. The proposed method also yields benefits with respect to the quality of the speckle images by suppressing contributions of non-uniformly distributed specular reflections.

Citations

65 citations in Web of Science®
76 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

271 downloads since deposited on 29 Sep 2009
68 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Nuclear Medicine
04 Faculty of Medicine > Institute of Pharmacology and Toxicology
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Language:English
Date:August 2009
Deposited On:29 Sep 2009 14:35
Last Modified:05 Apr 2016 13:21
Publisher:Optical Society of America (OSA)
ISSN:1094-4087
Publisher DOI:10.1364/OE.17.013904
PubMed ID:19654798
Permanent URL: http://doi.org/10.5167/uzh-20978

Download

[img]
Preview
Filetype: PDF
Size: 1MB
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations