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Comprehensive Retinal Image Analysis for Aggressive Posterior Retinopathy of Prematurity
Computer aided analysis plays a nontrivial role in assisting the diagnosis of various eye pathologies. In this paper, we propose a framework to help diagnose the presence of Aggressive Posterior Retinopathy Of Prematurity (APROP), a pathology that is characterised by rapid onset and increased tortuo...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5053412/ https://www.ncbi.nlm.nih.gov/pubmed/27711231 http://dx.doi.org/10.1371/journal.pone.0163923 |
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author | Rajashekar, Deepthi Srinivasa, Gowri Vinekar, Anand |
author_facet | Rajashekar, Deepthi Srinivasa, Gowri Vinekar, Anand |
author_sort | Rajashekar, Deepthi |
collection | PubMed |
description | Computer aided analysis plays a nontrivial role in assisting the diagnosis of various eye pathologies. In this paper, we propose a framework to help diagnose the presence of Aggressive Posterior Retinopathy Of Prematurity (APROP), a pathology that is characterised by rapid onset and increased tortuosity of blood vessels close to the optic disc (OD). We quantify vessel characteristics that are of clinical relevance to APROP such as tortuosity and the extent of branching i.e., vessel segment count in the defined diagnostic region. We have adapted three vessel segmentation techniques: matched filter response, scale space theory and morphology with local entropy based thresholding. The proposed feature set equips us to build a linear discriminant classifier to discriminate APROP images from clinically healthy images. We have studied 36 images from 21 APROP subjects against a control group of 15 clinically healthy age matched infants. All subjects are age matched ranging from 33−40 weeks of post menstrual age. Experimental results show that we attain 100% recall and 95.45% precision, when the vessel network obtained from morphology is used for feature extraction. |
format | Online Article Text |
id | pubmed-5053412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-50534122016-10-27 Comprehensive Retinal Image Analysis for Aggressive Posterior Retinopathy of Prematurity Rajashekar, Deepthi Srinivasa, Gowri Vinekar, Anand PLoS One Research Article Computer aided analysis plays a nontrivial role in assisting the diagnosis of various eye pathologies. In this paper, we propose a framework to help diagnose the presence of Aggressive Posterior Retinopathy Of Prematurity (APROP), a pathology that is characterised by rapid onset and increased tortuosity of blood vessels close to the optic disc (OD). We quantify vessel characteristics that are of clinical relevance to APROP such as tortuosity and the extent of branching i.e., vessel segment count in the defined diagnostic region. We have adapted three vessel segmentation techniques: matched filter response, scale space theory and morphology with local entropy based thresholding. The proposed feature set equips us to build a linear discriminant classifier to discriminate APROP images from clinically healthy images. We have studied 36 images from 21 APROP subjects against a control group of 15 clinically healthy age matched infants. All subjects are age matched ranging from 33−40 weeks of post menstrual age. Experimental results show that we attain 100% recall and 95.45% precision, when the vessel network obtained from morphology is used for feature extraction. Public Library of Science 2016-10-06 /pmc/articles/PMC5053412/ /pubmed/27711231 http://dx.doi.org/10.1371/journal.pone.0163923 Text en © 2016 Rajashekar et al http://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/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Rajashekar, Deepthi Srinivasa, Gowri Vinekar, Anand Comprehensive Retinal Image Analysis for Aggressive Posterior Retinopathy of Prematurity |
title | Comprehensive Retinal Image Analysis for Aggressive Posterior Retinopathy of Prematurity |
title_full | Comprehensive Retinal Image Analysis for Aggressive Posterior Retinopathy of Prematurity |
title_fullStr | Comprehensive Retinal Image Analysis for Aggressive Posterior Retinopathy of Prematurity |
title_full_unstemmed | Comprehensive Retinal Image Analysis for Aggressive Posterior Retinopathy of Prematurity |
title_short | Comprehensive Retinal Image Analysis for Aggressive Posterior Retinopathy of Prematurity |
title_sort | comprehensive retinal image analysis for aggressive posterior retinopathy of prematurity |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5053412/ https://www.ncbi.nlm.nih.gov/pubmed/27711231 http://dx.doi.org/10.1371/journal.pone.0163923 |
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