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An innovative strategy for standardized, structured, and interoperable results in ophthalmic examinations

BACKGROUND: Although ophthalmic devices have made remarkable progress and are widely used, most lack standardization of both image review and results reporting systems, making interoperability unachievable. We developed and validated new software for extracting, transforming, and storing information...

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Autores principales: Mun, Yongseok, Kim, Jooyoung, Noh, Kyoung Jin, Lee, Soochahn, Kim, Seok, Yi, Soyoung, Park, Kyu Hyung, Yoo, Sooyoung, Chang, Dong Jin, Park, Sang Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789748/
https://www.ncbi.nlm.nih.gov/pubmed/33407448
http://dx.doi.org/10.1186/s12911-020-01370-0
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author Mun, Yongseok
Kim, Jooyoung
Noh, Kyoung Jin
Lee, Soochahn
Kim, Seok
Yi, Soyoung
Park, Kyu Hyung
Yoo, Sooyoung
Chang, Dong Jin
Park, Sang Jun
author_facet Mun, Yongseok
Kim, Jooyoung
Noh, Kyoung Jin
Lee, Soochahn
Kim, Seok
Yi, Soyoung
Park, Kyu Hyung
Yoo, Sooyoung
Chang, Dong Jin
Park, Sang Jun
author_sort Mun, Yongseok
collection PubMed
description BACKGROUND: Although ophthalmic devices have made remarkable progress and are widely used, most lack standardization of both image review and results reporting systems, making interoperability unachievable. We developed and validated new software for extracting, transforming, and storing information from report images produced by ophthalmic examination devices to generate standardized, structured, and interoperable information to assist ophthalmologists in eye clinics. RESULTS: We selected report images derived from optical coherence tomography (OCT). The new software consists of three parts: (1) The Area Explorer, which determines whether the designated area in the configuration file contains numeric values or tomographic images; (2) The Value Reader, which converts images to text according to ophthalmic measurements; and (3) The Finding Classifier, which classifies pathologic findings from tomographic images included in the report. After assessment of Value Reader accuracy by human experts, all report images were converted and stored in a database. We applied the Value Reader, which achieved 99.67% accuracy, to a total of 433,175 OCT report images acquired in a single tertiary hospital from 07/04/2006 to 08/31/2019. The Finding Classifier provided pathologic findings (e.g., macular edema and subretinal fluid) and disease activity. Patient longitudinal data could be easily reviewed to document changes in measurements over time. The final results were loaded into a common data model (CDM), and the cropped tomographic images were loaded into the Picture Archive Communication System. CONCLUSIONS: The newly developed software extracts valuable information from OCT images and may be extended to other types of report image files produced by medical devices. Furthermore, powerful databases such as the CDM may be implemented or augmented by adding the information captured through our program.
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spelling pubmed-77897482021-01-07 An innovative strategy for standardized, structured, and interoperable results in ophthalmic examinations Mun, Yongseok Kim, Jooyoung Noh, Kyoung Jin Lee, Soochahn Kim, Seok Yi, Soyoung Park, Kyu Hyung Yoo, Sooyoung Chang, Dong Jin Park, Sang Jun BMC Med Inform Decis Mak Software BACKGROUND: Although ophthalmic devices have made remarkable progress and are widely used, most lack standardization of both image review and results reporting systems, making interoperability unachievable. We developed and validated new software for extracting, transforming, and storing information from report images produced by ophthalmic examination devices to generate standardized, structured, and interoperable information to assist ophthalmologists in eye clinics. RESULTS: We selected report images derived from optical coherence tomography (OCT). The new software consists of three parts: (1) The Area Explorer, which determines whether the designated area in the configuration file contains numeric values or tomographic images; (2) The Value Reader, which converts images to text according to ophthalmic measurements; and (3) The Finding Classifier, which classifies pathologic findings from tomographic images included in the report. After assessment of Value Reader accuracy by human experts, all report images were converted and stored in a database. We applied the Value Reader, which achieved 99.67% accuracy, to a total of 433,175 OCT report images acquired in a single tertiary hospital from 07/04/2006 to 08/31/2019. The Finding Classifier provided pathologic findings (e.g., macular edema and subretinal fluid) and disease activity. Patient longitudinal data could be easily reviewed to document changes in measurements over time. The final results were loaded into a common data model (CDM), and the cropped tomographic images were loaded into the Picture Archive Communication System. CONCLUSIONS: The newly developed software extracts valuable information from OCT images and may be extended to other types of report image files produced by medical devices. Furthermore, powerful databases such as the CDM may be implemented or augmented by adding the information captured through our program. BioMed Central 2021-01-06 /pmc/articles/PMC7789748/ /pubmed/33407448 http://dx.doi.org/10.1186/s12911-020-01370-0 Text en © The Author(s) 2020 Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
Mun, Yongseok
Kim, Jooyoung
Noh, Kyoung Jin
Lee, Soochahn
Kim, Seok
Yi, Soyoung
Park, Kyu Hyung
Yoo, Sooyoung
Chang, Dong Jin
Park, Sang Jun
An innovative strategy for standardized, structured, and interoperable results in ophthalmic examinations
title An innovative strategy for standardized, structured, and interoperable results in ophthalmic examinations
title_full An innovative strategy for standardized, structured, and interoperable results in ophthalmic examinations
title_fullStr An innovative strategy for standardized, structured, and interoperable results in ophthalmic examinations
title_full_unstemmed An innovative strategy for standardized, structured, and interoperable results in ophthalmic examinations
title_short An innovative strategy for standardized, structured, and interoperable results in ophthalmic examinations
title_sort innovative strategy for standardized, structured, and interoperable results in ophthalmic examinations
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789748/
https://www.ncbi.nlm.nih.gov/pubmed/33407448
http://dx.doi.org/10.1186/s12911-020-01370-0
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