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Fluorescence imaging reversion using spatially variant deconvolution
Fluorescence imaging opens new possibilities for intraoperative guidance and early cancer detection, in particular when using agents that target specific disease features. Nevertheless, photon scattering in tissue degrades image quality and leads to ambiguity in fluorescence image interpretation and...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889134/ https://www.ncbi.nlm.nih.gov/pubmed/31792293 http://dx.doi.org/10.1038/s41598-019-54578-0 |
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author | Anastasopoulou, Maria Gorpas, Dimitris Koch, Maximilian Liapis, Evangelos Glasl, Sarah Klemm, Uwe Karlas, Angelos Lasser, Tobias Ntziachristos, Vasilis |
author_facet | Anastasopoulou, Maria Gorpas, Dimitris Koch, Maximilian Liapis, Evangelos Glasl, Sarah Klemm, Uwe Karlas, Angelos Lasser, Tobias Ntziachristos, Vasilis |
author_sort | Anastasopoulou, Maria |
collection | PubMed |
description | Fluorescence imaging opens new possibilities for intraoperative guidance and early cancer detection, in particular when using agents that target specific disease features. Nevertheless, photon scattering in tissue degrades image quality and leads to ambiguity in fluorescence image interpretation and challenges clinical translation. We introduce the concept of capturing the spatially-dependent impulse response of an image and investigate Spatially Adaptive Impulse Response Correction (SAIRC), a method that is proposed for improving the accuracy and sensitivity achieved. Unlike classical methods that presume a homogeneous spatial distribution of optical properties in tissue, SAIRC explicitly measures the optical heterogeneity in tissues. This information allows, for the first time, the application of spatially-dependent deconvolution to correct the fluorescence images captured in relation to their modification by photon scatter. Using experimental measurements from phantoms and animals, we investigate the improvement in resolution and quantification over non-corrected images. We discuss how the proposed method is essential for maximizing the performance of fluorescence molecular imaging in the clinic. |
format | Online Article Text |
id | pubmed-6889134 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-68891342019-12-10 Fluorescence imaging reversion using spatially variant deconvolution Anastasopoulou, Maria Gorpas, Dimitris Koch, Maximilian Liapis, Evangelos Glasl, Sarah Klemm, Uwe Karlas, Angelos Lasser, Tobias Ntziachristos, Vasilis Sci Rep Article Fluorescence imaging opens new possibilities for intraoperative guidance and early cancer detection, in particular when using agents that target specific disease features. Nevertheless, photon scattering in tissue degrades image quality and leads to ambiguity in fluorescence image interpretation and challenges clinical translation. We introduce the concept of capturing the spatially-dependent impulse response of an image and investigate Spatially Adaptive Impulse Response Correction (SAIRC), a method that is proposed for improving the accuracy and sensitivity achieved. Unlike classical methods that presume a homogeneous spatial distribution of optical properties in tissue, SAIRC explicitly measures the optical heterogeneity in tissues. This information allows, for the first time, the application of spatially-dependent deconvolution to correct the fluorescence images captured in relation to their modification by photon scatter. Using experimental measurements from phantoms and animals, we investigate the improvement in resolution and quantification over non-corrected images. We discuss how the proposed method is essential for maximizing the performance of fluorescence molecular imaging in the clinic. Nature Publishing Group UK 2019-12-02 /pmc/articles/PMC6889134/ /pubmed/31792293 http://dx.doi.org/10.1038/s41598-019-54578-0 Text en © The Author(s) 2019 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Anastasopoulou, Maria Gorpas, Dimitris Koch, Maximilian Liapis, Evangelos Glasl, Sarah Klemm, Uwe Karlas, Angelos Lasser, Tobias Ntziachristos, Vasilis Fluorescence imaging reversion using spatially variant deconvolution |
title | Fluorescence imaging reversion using spatially variant deconvolution |
title_full | Fluorescence imaging reversion using spatially variant deconvolution |
title_fullStr | Fluorescence imaging reversion using spatially variant deconvolution |
title_full_unstemmed | Fluorescence imaging reversion using spatially variant deconvolution |
title_short | Fluorescence imaging reversion using spatially variant deconvolution |
title_sort | fluorescence imaging reversion using spatially variant deconvolution |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889134/ https://www.ncbi.nlm.nih.gov/pubmed/31792293 http://dx.doi.org/10.1038/s41598-019-54578-0 |
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