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Standardized quality metric system for structural brain magnetic resonance images in multi-center neuroimaging study
BACKGROUND: Multi-site neuroimaging offer several benefits and poses tough challenges in the drug development process. Although MRI protocol and clinical guidelines developed to address these challenges recommend the use of good quality images, reliable assessment of image quality is hampered by the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6142697/ https://www.ncbi.nlm.nih.gov/pubmed/30223797 http://dx.doi.org/10.1186/s12880-018-0266-4 |
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author | Osadebey, Michael E. Pedersen, Marius Arnold, Douglas L. Wendel-Mitoraj, Katrina E. Alzheimer’s Disease Neuroimaging Initiative, for the |
author_facet | Osadebey, Michael E. Pedersen, Marius Arnold, Douglas L. Wendel-Mitoraj, Katrina E. Alzheimer’s Disease Neuroimaging Initiative, for the |
author_sort | Osadebey, Michael E. |
collection | PubMed |
description | BACKGROUND: Multi-site neuroimaging offer several benefits and poses tough challenges in the drug development process. Although MRI protocol and clinical guidelines developed to address these challenges recommend the use of good quality images, reliable assessment of image quality is hampered by the several shortcomings of existing techniques. METHODS: Given a test image two feature images are extracted. They are grayscale and contrast feature images. Four binary images are generated by setting four different global thresholds on the feature images. Image quality is predicted by measuring the structural similarity between appropriate pairs of binary images. The lower and upper limits of the quality index are 0 and 1. Quality prediction is based on four quality attributes; luminance contrast, texture, texture contrast and lightness. RESULTS: Performance evaluation on test data from three multi-site clinical trials show good objective quality evaluation across MRI sequences, levels of distortion and quality attributes. Correlation with subjective evaluation by human observers is ≥ 0.6. CONCLUSION: The results are promising for the evaluation of MRI protocols, specifically the standardization of quality index, designed to overcome the challenges encountered in multi-site clinical trials. |
format | Online Article Text |
id | pubmed-6142697 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61426972018-09-21 Standardized quality metric system for structural brain magnetic resonance images in multi-center neuroimaging study Osadebey, Michael E. Pedersen, Marius Arnold, Douglas L. Wendel-Mitoraj, Katrina E. Alzheimer’s Disease Neuroimaging Initiative, for the BMC Med Imaging Research Article BACKGROUND: Multi-site neuroimaging offer several benefits and poses tough challenges in the drug development process. Although MRI protocol and clinical guidelines developed to address these challenges recommend the use of good quality images, reliable assessment of image quality is hampered by the several shortcomings of existing techniques. METHODS: Given a test image two feature images are extracted. They are grayscale and contrast feature images. Four binary images are generated by setting four different global thresholds on the feature images. Image quality is predicted by measuring the structural similarity between appropriate pairs of binary images. The lower and upper limits of the quality index are 0 and 1. Quality prediction is based on four quality attributes; luminance contrast, texture, texture contrast and lightness. RESULTS: Performance evaluation on test data from three multi-site clinical trials show good objective quality evaluation across MRI sequences, levels of distortion and quality attributes. Correlation with subjective evaluation by human observers is ≥ 0.6. CONCLUSION: The results are promising for the evaluation of MRI protocols, specifically the standardization of quality index, designed to overcome the challenges encountered in multi-site clinical trials. BioMed Central 2018-09-17 /pmc/articles/PMC6142697/ /pubmed/30223797 http://dx.doi.org/10.1186/s12880-018-0266-4 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 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. |
spellingShingle | Research Article Osadebey, Michael E. Pedersen, Marius Arnold, Douglas L. Wendel-Mitoraj, Katrina E. Alzheimer’s Disease Neuroimaging Initiative, for the Standardized quality metric system for structural brain magnetic resonance images in multi-center neuroimaging study |
title | Standardized quality metric system for structural brain magnetic resonance images in multi-center neuroimaging study |
title_full | Standardized quality metric system for structural brain magnetic resonance images in multi-center neuroimaging study |
title_fullStr | Standardized quality metric system for structural brain magnetic resonance images in multi-center neuroimaging study |
title_full_unstemmed | Standardized quality metric system for structural brain magnetic resonance images in multi-center neuroimaging study |
title_short | Standardized quality metric system for structural brain magnetic resonance images in multi-center neuroimaging study |
title_sort | standardized quality metric system for structural brain magnetic resonance images in multi-center neuroimaging study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6142697/ https://www.ncbi.nlm.nih.gov/pubmed/30223797 http://dx.doi.org/10.1186/s12880-018-0266-4 |
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