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A scalable open-source MATLAB toolbox for reconstruction and analysis of multispectral optoacoustic tomography data

Multispectral photoacoustic tomography enables the resolution of spectral components of a tissue or sample at high spatiotemporal resolution. With the availability of commercial instruments, the acquisition of data using this modality has become consistent and standardized. However, the analysis of...

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Autores principales: O’Kelly, Devin, Campbell, James, Gerberich, Jeni L., Karbasi, Paniz, Malladi, Venkat, Jamieson, Andrew, Wang, Liqiang, Mason, Ralph P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494751/
https://www.ncbi.nlm.nih.gov/pubmed/34615891
http://dx.doi.org/10.1038/s41598-021-97726-1
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author O’Kelly, Devin
Campbell, James
Gerberich, Jeni L.
Karbasi, Paniz
Malladi, Venkat
Jamieson, Andrew
Wang, Liqiang
Mason, Ralph P.
author_facet O’Kelly, Devin
Campbell, James
Gerberich, Jeni L.
Karbasi, Paniz
Malladi, Venkat
Jamieson, Andrew
Wang, Liqiang
Mason, Ralph P.
author_sort O’Kelly, Devin
collection PubMed
description Multispectral photoacoustic tomography enables the resolution of spectral components of a tissue or sample at high spatiotemporal resolution. With the availability of commercial instruments, the acquisition of data using this modality has become consistent and standardized. However, the analysis of such data is often hampered by opaque processing algorithms, which are challenging to verify and validate from a user perspective. Furthermore, such tools are inflexible, often locking users into a restricted set of processing motifs, which may not be able to accommodate the demands of diverse experiments. To address these needs, we have developed a Reconstruction, Analysis, and Filtering Toolbox to support the analysis of photoacoustic imaging data. The toolbox includes several algorithms to improve the overall quantification of photoacoustic imaging, including non-negative constraints and multispectral filters. We demonstrate various use cases, including dynamic imaging challenges and quantification of drug effect, and describe the ability of the toolbox to be parallelized on a high performance computing cluster.
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spelling pubmed-84947512021-10-07 A scalable open-source MATLAB toolbox for reconstruction and analysis of multispectral optoacoustic tomography data O’Kelly, Devin Campbell, James Gerberich, Jeni L. Karbasi, Paniz Malladi, Venkat Jamieson, Andrew Wang, Liqiang Mason, Ralph P. Sci Rep Article Multispectral photoacoustic tomography enables the resolution of spectral components of a tissue or sample at high spatiotemporal resolution. With the availability of commercial instruments, the acquisition of data using this modality has become consistent and standardized. However, the analysis of such data is often hampered by opaque processing algorithms, which are challenging to verify and validate from a user perspective. Furthermore, such tools are inflexible, often locking users into a restricted set of processing motifs, which may not be able to accommodate the demands of diverse experiments. To address these needs, we have developed a Reconstruction, Analysis, and Filtering Toolbox to support the analysis of photoacoustic imaging data. The toolbox includes several algorithms to improve the overall quantification of photoacoustic imaging, including non-negative constraints and multispectral filters. We demonstrate various use cases, including dynamic imaging challenges and quantification of drug effect, and describe the ability of the toolbox to be parallelized on a high performance computing cluster. Nature Publishing Group UK 2021-10-06 /pmc/articles/PMC8494751/ /pubmed/34615891 http://dx.doi.org/10.1038/s41598-021-97726-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
O’Kelly, Devin
Campbell, James
Gerberich, Jeni L.
Karbasi, Paniz
Malladi, Venkat
Jamieson, Andrew
Wang, Liqiang
Mason, Ralph P.
A scalable open-source MATLAB toolbox for reconstruction and analysis of multispectral optoacoustic tomography data
title A scalable open-source MATLAB toolbox for reconstruction and analysis of multispectral optoacoustic tomography data
title_full A scalable open-source MATLAB toolbox for reconstruction and analysis of multispectral optoacoustic tomography data
title_fullStr A scalable open-source MATLAB toolbox for reconstruction and analysis of multispectral optoacoustic tomography data
title_full_unstemmed A scalable open-source MATLAB toolbox for reconstruction and analysis of multispectral optoacoustic tomography data
title_short A scalable open-source MATLAB toolbox for reconstruction and analysis of multispectral optoacoustic tomography data
title_sort scalable open-source matlab toolbox for reconstruction and analysis of multispectral optoacoustic tomography data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494751/
https://www.ncbi.nlm.nih.gov/pubmed/34615891
http://dx.doi.org/10.1038/s41598-021-97726-1
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