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Exploratory Dijkstra forest based automatic vessel segmentation: applications in video indirect ophthalmoscopy (VIO)

We present a methodology for extracting the vascular network in the human retina using Dijkstra’s shortest-path algorithm. Our method preserves vessel thickness, requires no manual intervention, and follows vessel branching naturally and efficiently. To test our method, we constructed a retinal vide...

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Detalles Bibliográficos
Autores principales: Estrada, Rolando, Tomasi, Carlo, Cabrera, Michelle T., Wallace, David K., Freedman, Sharon F., Farsiu, Sina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Optical Society of America 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3269849/
https://www.ncbi.nlm.nih.gov/pubmed/22312585
http://dx.doi.org/10.1364/BOE.3.000327
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author Estrada, Rolando
Tomasi, Carlo
Cabrera, Michelle T.
Wallace, David K.
Freedman, Sharon F.
Farsiu, Sina
author_facet Estrada, Rolando
Tomasi, Carlo
Cabrera, Michelle T.
Wallace, David K.
Freedman, Sharon F.
Farsiu, Sina
author_sort Estrada, Rolando
collection PubMed
description We present a methodology for extracting the vascular network in the human retina using Dijkstra’s shortest-path algorithm. Our method preserves vessel thickness, requires no manual intervention, and follows vessel branching naturally and efficiently. To test our method, we constructed a retinal video indirect ophthalmoscopy (VIO) image database from pediatric patients and compared the segmentations achieved by our method and state-of-the-art approaches to a human-drawn gold standard. Our experimental results show that our algorithm outperforms prior state-of-the-art methods, for both single VIO frames and automatically generated, large field-of-view enhanced mosaics. We have made the corresponding dataset and source code freely available online.
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spelling pubmed-32698492012-02-06 Exploratory Dijkstra forest based automatic vessel segmentation: applications in video indirect ophthalmoscopy (VIO) Estrada, Rolando Tomasi, Carlo Cabrera, Michelle T. Wallace, David K. Freedman, Sharon F. Farsiu, Sina Biomed Opt Express Image Processing We present a methodology for extracting the vascular network in the human retina using Dijkstra’s shortest-path algorithm. Our method preserves vessel thickness, requires no manual intervention, and follows vessel branching naturally and efficiently. To test our method, we constructed a retinal video indirect ophthalmoscopy (VIO) image database from pediatric patients and compared the segmentations achieved by our method and state-of-the-art approaches to a human-drawn gold standard. Our experimental results show that our algorithm outperforms prior state-of-the-art methods, for both single VIO frames and automatically generated, large field-of-view enhanced mosaics. We have made the corresponding dataset and source code freely available online. Optical Society of America 2012-01-18 /pmc/articles/PMC3269849/ /pubmed/22312585 http://dx.doi.org/10.1364/BOE.3.000327 Text en © 2012 Optical Society of America http://creativecommons.org/licenses/by-nc-nd/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 Unported License, which permits download and redistribution, provided that the original work is properly cited. This license restricts the article from being modified or used commercially.
spellingShingle Image Processing
Estrada, Rolando
Tomasi, Carlo
Cabrera, Michelle T.
Wallace, David K.
Freedman, Sharon F.
Farsiu, Sina
Exploratory Dijkstra forest based automatic vessel segmentation: applications in video indirect ophthalmoscopy (VIO)
title Exploratory Dijkstra forest based automatic vessel segmentation: applications in video indirect ophthalmoscopy (VIO)
title_full Exploratory Dijkstra forest based automatic vessel segmentation: applications in video indirect ophthalmoscopy (VIO)
title_fullStr Exploratory Dijkstra forest based automatic vessel segmentation: applications in video indirect ophthalmoscopy (VIO)
title_full_unstemmed Exploratory Dijkstra forest based automatic vessel segmentation: applications in video indirect ophthalmoscopy (VIO)
title_short Exploratory Dijkstra forest based automatic vessel segmentation: applications in video indirect ophthalmoscopy (VIO)
title_sort exploratory dijkstra forest based automatic vessel segmentation: applications in video indirect ophthalmoscopy (vio)
topic Image Processing
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3269849/
https://www.ncbi.nlm.nih.gov/pubmed/22312585
http://dx.doi.org/10.1364/BOE.3.000327
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