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Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis
A multi-parameter quantification method was implemented to quantify retinal vascular injuries in microscopic images of clinically relevant eye diseases. This method was applied to wholemount retinal trypsin digest images of diabetic Akita/+, and bcl-2 knocked out mice models. Five unique features of...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4855887/ https://www.ncbi.nlm.nih.gov/pubmed/27186534 |
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author | Ghanian, Zahra Staniszewski, Kevin Jamali, Nasim Sepehr, Reyhaneh Wang, Shoujian Sorenson, Christine M. Sheibani, Nader Ranji, Mahsa |
author_facet | Ghanian, Zahra Staniszewski, Kevin Jamali, Nasim Sepehr, Reyhaneh Wang, Shoujian Sorenson, Christine M. Sheibani, Nader Ranji, Mahsa |
author_sort | Ghanian, Zahra |
collection | PubMed |
description | A multi-parameter quantification method was implemented to quantify retinal vascular injuries in microscopic images of clinically relevant eye diseases. This method was applied to wholemount retinal trypsin digest images of diabetic Akita/+, and bcl-2 knocked out mice models. Five unique features of retinal vasculature were extracted to monitor early structural changes and retinopathy, as well as quantifying the disease progression. Our approach was validated through simulations of retinal images. Results showed fewer number of cells (P = 5.1205e-05), greater population ratios of endothelial cells to pericytes (PCs) (P = 5.1772e-04; an indicator of PC loss), higher fractal dimension (P = 8.2202e-05), smaller vessel coverage (P = 1.4214e-05), and greater number of acellular capillaries (P = 7.0414e-04) for diabetic retina as compared to normal retina. Quantification using the present method would be helpful in evaluating physiological and pathological retinopathy in a high-throughput and reproducible manner. |
format | Online Article Text |
id | pubmed-4855887 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-48558872016-05-16 Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis Ghanian, Zahra Staniszewski, Kevin Jamali, Nasim Sepehr, Reyhaneh Wang, Shoujian Sorenson, Christine M. Sheibani, Nader Ranji, Mahsa J Med Signals Sens Original Article A multi-parameter quantification method was implemented to quantify retinal vascular injuries in microscopic images of clinically relevant eye diseases. This method was applied to wholemount retinal trypsin digest images of diabetic Akita/+, and bcl-2 knocked out mice models. Five unique features of retinal vasculature were extracted to monitor early structural changes and retinopathy, as well as quantifying the disease progression. Our approach was validated through simulations of retinal images. Results showed fewer number of cells (P = 5.1205e-05), greater population ratios of endothelial cells to pericytes (PCs) (P = 5.1772e-04; an indicator of PC loss), higher fractal dimension (P = 8.2202e-05), smaller vessel coverage (P = 1.4214e-05), and greater number of acellular capillaries (P = 7.0414e-04) for diabetic retina as compared to normal retina. Quantification using the present method would be helpful in evaluating physiological and pathological retinopathy in a high-throughput and reproducible manner. Medknow Publications & Media Pvt Ltd 2016 /pmc/articles/PMC4855887/ /pubmed/27186534 Text en Copyright: © 2016 Journal of Medical Signals & Sensors http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms. |
spellingShingle | Original Article Ghanian, Zahra Staniszewski, Kevin Jamali, Nasim Sepehr, Reyhaneh Wang, Shoujian Sorenson, Christine M. Sheibani, Nader Ranji, Mahsa Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis |
title | Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis |
title_full | Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis |
title_fullStr | Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis |
title_full_unstemmed | Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis |
title_short | Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis |
title_sort | quantitative assessment of retinopathy using multi-parameter image analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4855887/ https://www.ncbi.nlm.nih.gov/pubmed/27186534 |
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