Arteriolar-to-venular diameter ratio estimation: A pixel-parallel approach

C. Alonso-Montes; M. G. Penedo; D. L. Vilariño

doi:10.1109/CNNA.2008.4588655

Arteriolar-to-venular diameter ratio estimation: A pixel-parallel approach

C. Alonso-Montes^*
, M. G. Penedo
, D. L. Vilariño

^*Autor correspondiente de este trabajo

University of A Coruna
University of Santiago de Compostela

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

2 Citas (Scopus)

Resumen

The study of blood vessel features plays an important role in order to characterise markers used in early disease diagnosis. The arteriolar-to-venular (AVR) diameter ratio is an earlier marker related with cardiovascular risk, hypertension and diabetes. The extraction of the retinal vessel tree is not only the main task related with those medical applications intended to compute the AVR ratio, but it also implies a high computation effort. From the image processing point of view, many strategies and algorithms have been developed to deal with the extraction of this retinal vessel tree but specially regarding on the accuracy, but the execution time is still an open problem. In this paper, a methodology to extract the retinal vessel tree, tested in a fine-grain pixel-parallel processor array, is integrated into an application for the estimation of the AVR ratio in angiographies.

Idioma original	Inglés
Título de la publicación alojada	2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures
Páginas	86-91
Número de páginas	6
DOI	https://doi.org/10.1109/CNNA.2008.4588655
Estado	Publicada - 2008
Publicado de forma externa	Sí
Evento	2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures - Santiago de Compostela, Espana Duración: 14 jul 2008 → 16 jul 2008

Serie de la publicación

Nombre	Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications

Conferencia

Conferencia	2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures
País/Territorio	Espana
Ciudad	Santiago de Compostela
Período	14/07/08 → 16/07/08

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 3: Salud y bienestar

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10.1109/CNNA.2008.4588655

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Alonso-Montes, C., Penedo, M. G., & Vilariño, D. L. (2008). Arteriolar-to-venular diameter ratio estimation: A pixel-parallel approach. En 2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures (pp. 86-91). Artículo 4588655 (Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications). https://doi.org/10.1109/CNNA.2008.4588655

Alonso-Montes, C. ; Penedo, M. G. ; Vilariño, D. L. / Arteriolar-to-venular diameter ratio estimation : A pixel-parallel approach. 2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures. 2008. pp. 86-91 (Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications).

@inproceedings{fc6b9093edc14deaad4750dc9a8fe9fc,

title = "Arteriolar-to-venular diameter ratio estimation: A pixel-parallel approach",

abstract = "The study of blood vessel features plays an important role in order to characterise markers used in early disease diagnosis. The arteriolar-to-venular (AVR) diameter ratio is an earlier marker related with cardiovascular risk, hypertension and diabetes. The extraction of the retinal vessel tree is not only the main task related with those medical applications intended to compute the AVR ratio, but it also implies a high computation effort. From the image processing point of view, many strategies and algorithms have been developed to deal with the extraction of this retinal vessel tree but specially regarding on the accuracy, but the execution time is still an open problem. In this paper, a methodology to extract the retinal vessel tree, tested in a fine-grain pixel-parallel processor array, is integrated into an application for the estimation of the AVR ratio in angiographies.",

author = "C. Alonso-Montes and Penedo, \{M. G.\} and Vilari{\~n}o, \{D. L.\}",

year = "2008",

doi = "10.1109/CNNA.2008.4588655",

language = "English",

isbn = "9781424420902",

series = "Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications",

pages = "86--91",

booktitle = "2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures",

note = "2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures ; Conference date: 14-07-2008 Through 16-07-2008",

}

Alonso-Montes, C, Penedo, MG & Vilariño, DL 2008, Arteriolar-to-venular diameter ratio estimation: A pixel-parallel approach. En 2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures., 4588655, Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications, pp. 86-91, 2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures, Santiago de Compostela, Espana, 14/07/08. https://doi.org/10.1109/CNNA.2008.4588655

Arteriolar-to-venular diameter ratio estimation: A pixel-parallel approach. / Alonso-Montes, C.; Penedo, M. G.; Vilariño, D. L.
2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures. 2008. p. 86-91 4588655 (Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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T1 - Arteriolar-to-venular diameter ratio estimation

T2 - 2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures

AU - Alonso-Montes, C.

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Y1 - 2008

N2 - The study of blood vessel features plays an important role in order to characterise markers used in early disease diagnosis. The arteriolar-to-venular (AVR) diameter ratio is an earlier marker related with cardiovascular risk, hypertension and diabetes. The extraction of the retinal vessel tree is not only the main task related with those medical applications intended to compute the AVR ratio, but it also implies a high computation effort. From the image processing point of view, many strategies and algorithms have been developed to deal with the extraction of this retinal vessel tree but specially regarding on the accuracy, but the execution time is still an open problem. In this paper, a methodology to extract the retinal vessel tree, tested in a fine-grain pixel-parallel processor array, is integrated into an application for the estimation of the AVR ratio in angiographies.

AB - The study of blood vessel features plays an important role in order to characterise markers used in early disease diagnosis. The arteriolar-to-venular (AVR) diameter ratio is an earlier marker related with cardiovascular risk, hypertension and diabetes. The extraction of the retinal vessel tree is not only the main task related with those medical applications intended to compute the AVR ratio, but it also implies a high computation effort. From the image processing point of view, many strategies and algorithms have been developed to deal with the extraction of this retinal vessel tree but specially regarding on the accuracy, but the execution time is still an open problem. In this paper, a methodology to extract the retinal vessel tree, tested in a fine-grain pixel-parallel processor array, is integrated into an application for the estimation of the AVR ratio in angiographies.

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Alonso-Montes C, Penedo MG, Vilariño DL. Arteriolar-to-venular diameter ratio estimation: A pixel-parallel approach. En 2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures. 2008. p. 86-91. 4588655. (Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications). doi: 10.1109/CNNA.2008.4588655

Arteriolar-to-venular diameter ratio estimation: A pixel-parallel approach

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