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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
Descripción
Sumario: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.