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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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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. |
format | Online Article Text |
id | pubmed-8494751 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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