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ALIGNING VIDEO-AND STRUCTURED DATA FOR IMAGING OPTIMISATION
Imaging optimisation can benefit from combining structured data with qualitative data in the form of audio and video recordings. Since video is complex to work with, there is a need to find a workable solution that minimises the additional time investment. The purpose of the paper is to outline a ge...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8507456/ https://www.ncbi.nlm.nih.gov/pubmed/34037218 http://dx.doi.org/10.1093/rpd/ncab071 |
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author | Ivarsson, Jonas Almén, Anja Falkenberg, Mårten Lundh, Charlotta Båth, Magnus |
author_facet | Ivarsson, Jonas Almén, Anja Falkenberg, Mårten Lundh, Charlotta Båth, Magnus |
author_sort | Ivarsson, Jonas |
collection | PubMed |
description | Imaging optimisation can benefit from combining structured data with qualitative data in the form of audio and video recordings. Since video is complex to work with, there is a need to find a workable solution that minimises the additional time investment. The purpose of the paper is to outline a general workflow that can begin to address this issue. What is described is a data management process comprising the three steps of collection, mining and contextualisation. This process offers a way to work systematically and at a large scale without succumbing to the context loss of statistical methods. The proposed workflow effectively combines the video and structured data to enable a new level of insights in the optimisation process. |
format | Online Article Text |
id | pubmed-8507456 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-85074562021-10-13 ALIGNING VIDEO-AND STRUCTURED DATA FOR IMAGING OPTIMISATION Ivarsson, Jonas Almén, Anja Falkenberg, Mårten Lundh, Charlotta Båth, Magnus Radiat Prot Dosimetry Paper Imaging optimisation can benefit from combining structured data with qualitative data in the form of audio and video recordings. Since video is complex to work with, there is a need to find a workable solution that minimises the additional time investment. The purpose of the paper is to outline a general workflow that can begin to address this issue. What is described is a data management process comprising the three steps of collection, mining and contextualisation. This process offers a way to work systematically and at a large scale without succumbing to the context loss of statistical methods. The proposed workflow effectively combines the video and structured data to enable a new level of insights in the optimisation process. Oxford University Press 2021-05-25 /pmc/articles/PMC8507456/ /pubmed/34037218 http://dx.doi.org/10.1093/rpd/ncab071 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Paper Ivarsson, Jonas Almén, Anja Falkenberg, Mårten Lundh, Charlotta Båth, Magnus ALIGNING VIDEO-AND STRUCTURED DATA FOR IMAGING OPTIMISATION |
title | ALIGNING VIDEO-AND STRUCTURED DATA FOR IMAGING OPTIMISATION |
title_full | ALIGNING VIDEO-AND STRUCTURED DATA FOR IMAGING OPTIMISATION |
title_fullStr | ALIGNING VIDEO-AND STRUCTURED DATA FOR IMAGING OPTIMISATION |
title_full_unstemmed | ALIGNING VIDEO-AND STRUCTURED DATA FOR IMAGING OPTIMISATION |
title_short | ALIGNING VIDEO-AND STRUCTURED DATA FOR IMAGING OPTIMISATION |
title_sort | aligning video-and structured data for imaging optimisation |
topic | Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8507456/ https://www.ncbi.nlm.nih.gov/pubmed/34037218 http://dx.doi.org/10.1093/rpd/ncab071 |
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