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Understanding Scanner Utilization With Real-Time DICOM Metadata Extraction

Understanding system performance metrics ensures better utilization of the radiology resources with more targeted interventions. The images produced by radiology scanners typically follow the DICOM (Digital Imaging and Communications in Medicine) standard format. The DICOM images consist of textual...

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Autores principales: KATHIRAVELU, PRADEEBAN, SHARMA, ASHISH, SHARMA, PUNEET
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9373881/
https://www.ncbi.nlm.nih.gov/pubmed/35966128
http://dx.doi.org/10.1109/access.2021.3050467
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author KATHIRAVELU, PRADEEBAN
SHARMA, ASHISH
SHARMA, PUNEET
author_facet KATHIRAVELU, PRADEEBAN
SHARMA, ASHISH
SHARMA, PUNEET
author_sort KATHIRAVELU, PRADEEBAN
collection PubMed
description Understanding system performance metrics ensures better utilization of the radiology resources with more targeted interventions. The images produced by radiology scanners typically follow the DICOM (Digital Imaging and Communications in Medicine) standard format. The DICOM images consist of textual metadata that can be used to calculate key timing parameters, such as the exact study durations and scanner utilization. However, hospital networks lack the resources and capabilities to extract the metadata from the images quickly and automatically compute the scanner utilization properties. Thus, they resort to using data records from the Radiology Information Systems (RIS). However, data acquired from RIS are prone to human errors, rendering many derived key performance metrics inadequate and inaccurate. Hence, there is motivation to establish a real-time image transfer from the Picture Archiving and Communication Systems (PACS) to receive the DICOM images from the scanners to research clusters to conduct such metadata processing to evaluate scanner utilization metrics efficiently and quickly. This paper analyzes the scanners’ utilization by developing a real-time monitoring framework that retrieves radiology images into a research cluster using the DICOM networking protocol and then extracts and processes the metadata from the images. Our proposed approach facilitates a better understanding of scanner utilization across a vast healthcare network by observing properties such as study duration, the interval between the encounters, and the series count of studies. Benchmarks against using the RIS data indicate that our proposed framework based on real-time PACS data estimates the scanner utilization more accurately. Furthermore, our framework has been running stable and performing its computation for more than two years on our extensive healthcare network in pseudo real-time.
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spelling pubmed-93738812022-08-12 Understanding Scanner Utilization With Real-Time DICOM Metadata Extraction KATHIRAVELU, PRADEEBAN SHARMA, ASHISH SHARMA, PUNEET IEEE Access Article Understanding system performance metrics ensures better utilization of the radiology resources with more targeted interventions. The images produced by radiology scanners typically follow the DICOM (Digital Imaging and Communications in Medicine) standard format. The DICOM images consist of textual metadata that can be used to calculate key timing parameters, such as the exact study durations and scanner utilization. However, hospital networks lack the resources and capabilities to extract the metadata from the images quickly and automatically compute the scanner utilization properties. Thus, they resort to using data records from the Radiology Information Systems (RIS). However, data acquired from RIS are prone to human errors, rendering many derived key performance metrics inadequate and inaccurate. Hence, there is motivation to establish a real-time image transfer from the Picture Archiving and Communication Systems (PACS) to receive the DICOM images from the scanners to research clusters to conduct such metadata processing to evaluate scanner utilization metrics efficiently and quickly. This paper analyzes the scanners’ utilization by developing a real-time monitoring framework that retrieves radiology images into a research cluster using the DICOM networking protocol and then extracts and processes the metadata from the images. Our proposed approach facilitates a better understanding of scanner utilization across a vast healthcare network by observing properties such as study duration, the interval between the encounters, and the series count of studies. Benchmarks against using the RIS data indicate that our proposed framework based on real-time PACS data estimates the scanner utilization more accurately. Furthermore, our framework has been running stable and performing its computation for more than two years on our extensive healthcare network in pseudo real-time. 2021 2021-01-11 /pmc/articles/PMC9373881/ /pubmed/35966128 http://dx.doi.org/10.1109/access.2021.3050467 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
spellingShingle Article
KATHIRAVELU, PRADEEBAN
SHARMA, ASHISH
SHARMA, PUNEET
Understanding Scanner Utilization With Real-Time DICOM Metadata Extraction
title Understanding Scanner Utilization With Real-Time DICOM Metadata Extraction
title_full Understanding Scanner Utilization With Real-Time DICOM Metadata Extraction
title_fullStr Understanding Scanner Utilization With Real-Time DICOM Metadata Extraction
title_full_unstemmed Understanding Scanner Utilization With Real-Time DICOM Metadata Extraction
title_short Understanding Scanner Utilization With Real-Time DICOM Metadata Extraction
title_sort understanding scanner utilization with real-time dicom metadata extraction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9373881/
https://www.ncbi.nlm.nih.gov/pubmed/35966128
http://dx.doi.org/10.1109/access.2021.3050467
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