Multi-channel deep tissue flowmetry based on temporal diffuse speckle contrast analysis
Recently, diffuse speckle contrast analysis (DSCA) was introduced as a competent modality for deep tissue blood flow measurement, where the speckle contrast is calculated over spatial domain on the CCD image of diffuse reflectance. In this paper, we introduce time-domain DSCA where temporal statisti...
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sg-ntu-dr.10356-1010332023-12-29T06:51:14Z Multi-channel deep tissue flowmetry based on temporal diffuse speckle contrast analysis Bi, Renzhe Dong, Jing Lee, Kijoon School of Chemical and Biomedical Engineering DRNTU::Engineering::Bioengineering Recently, diffuse speckle contrast analysis (DSCA) was introduced as a competent modality for deep tissue blood flow measurement, where the speckle contrast is calculated over spatial domain on the CCD image of diffuse reflectance. In this paper, we introduce time-domain DSCA where temporal statistics are used for speckle contrast calculation and results in the same deep tissue flow measurement. This new modality is especially suitable for multi-channel real-time flowmetry, and we demonstrate its performance on human arm during cuff occlusion test. Independent component analysis (ICA) study on multi-channel data shows promising results about underlying physiology. Published version 2013-12-18T01:59:15Z 2019-12-06T20:32:22Z 2013-12-18T01:59:15Z 2019-12-06T20:32:22Z 2013 2013 Journal Article Bi, R., Dong, J., & Lee, K. (2013). Multi-channel deep tissue flowmetry based on temporal diffuse speckle contrast analysis. Optics express, 21(19), 22854-22861. 1094-4087 https://hdl.handle.net/10356/101033 http://hdl.handle.net/10220/18296 10.1364/OE.21.022854 en Optics express © 2013 Optical Society of America. This paper was published in Optics Express and is made available as an electronic reprint (preprint) with permission of Optical Society of America. The paper can be found at the following official DOI: http://dx.doi.org/10.1364/OE.21.022854. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. application/pdf |
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DRNTU::Engineering::Bioengineering Bi, Renzhe Dong, Jing Lee, Kijoon Multi-channel deep tissue flowmetry based on temporal diffuse speckle contrast analysis |
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Recently, diffuse speckle contrast analysis (DSCA) was introduced as a competent modality for deep tissue blood flow measurement, where the speckle contrast is calculated over spatial domain on the CCD image of diffuse reflectance. In this paper, we introduce time-domain DSCA where temporal statistics are used for speckle contrast calculation and results in the same deep tissue flow measurement. This new modality is especially suitable for multi-channel real-time flowmetry, and we demonstrate its performance on human arm during cuff occlusion test. Independent component analysis (ICA) study on multi-channel data shows promising results about underlying physiology. |
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School of Chemical and Biomedical Engineering |
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School of Chemical and Biomedical Engineering Bi, Renzhe Dong, Jing Lee, Kijoon |
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Article |
author |
Bi, Renzhe Dong, Jing Lee, Kijoon |
author_sort |
Bi, Renzhe |
title |
Multi-channel deep tissue flowmetry based on temporal diffuse speckle contrast analysis |
title_short |
Multi-channel deep tissue flowmetry based on temporal diffuse speckle contrast analysis |
title_full |
Multi-channel deep tissue flowmetry based on temporal diffuse speckle contrast analysis |
title_fullStr |
Multi-channel deep tissue flowmetry based on temporal diffuse speckle contrast analysis |
title_full_unstemmed |
Multi-channel deep tissue flowmetry based on temporal diffuse speckle contrast analysis |
title_sort |
multi-channel deep tissue flowmetry based on temporal diffuse speckle contrast analysis |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/101033 http://hdl.handle.net/10220/18296 |
_version_ |
1787136703333400576 |