TY - JOUR
T1 - A scalable open-source MATLAB toolbox for reconstruction and analysis of multispectral optoacoustic tomography data
AU - O’Kelly, Devin
AU - Campbell, James
AU - Gerberich, Jeni L.
AU - Karbasi, Paniz
AU - Malladi, Venkat
AU - Jamieson, Andrew
AU - Wang, Liqiang
AU - Mason, Ralph P.
N1 - Funding Information:
We would like to acknowledge Stefan Morscher, Neal Burton, Jacob Tippetts, and Clinton Hupple of iThera Medical GmbH, for extensive assistance in organizing and validating the pipeline. We thank David Trudgian and Daniel Moser for their assistance in integrating the pipeline into the high performance computing environment. The research was supported in part by National Institutes of Health (NIH) Grant 1R01CA244579-01A1, Cancer Prevention and Research Institute of Texas (CPRIT) IIRA Grants RP140285 and RP140399 and the assistance of the Southwestern Small Animal Imaging Resource through the NIH Cancer Center Support Grant 1P30 CA142543. DOK was the recipient of a fellowship administered by the Lyda Hill Department of Bioinformatics. The iThera MSOT was purchased under NIH Grant 1 S10 OD018094-01A1.
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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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U2 - 10.1038/s41598-021-97726-1
DO - 10.1038/s41598-021-97726-1
M3 - Article
C2 - 34615891
AN - SCOPUS:85116475742
SN - 2045-2322
VL - 11
JO - Scientific reports
JF - Scientific reports
IS - 1
M1 - 19872
ER -