Methods for Automatic Glaucoma Detection and Feature Extraction by Different Techniques at the Pre-processing Stage in Fundus Images

Eduardo Guillermo Pinos Velez; Maria Isabel Cordero Mendieta; Roberto Francisco Coronel Berrezueta

doi:10.54941/ahfe1002691

Methods for Automatic Glaucoma Detection and Feature Extraction by Different Techniques at the Pre-processing Stage in Fundus Images

Título traducido de la contribución: Métodos para la detección automática de glaucoma y extracción de características mediante diferentes técnicas en la etapa de preprocesamiento en imágenes de fondo de ojo

Eduardo Guillermo Pinos Velez
, Maria Isabel Cordero Mendieta
, Roberto Francisco Coronel Berrezueta

Producción científica: Contribución a una conferencia › Documento

Resumen

El glaucoma es una enfermedad neurodegenerativa, progresiva y silenciosa que afecta al nervio óptico, caracterizada por un aumento de la presión intraocular que provoca daños irreversibles en el nervio óptico. La dificultad en el diagnóstico precoz del glaucoma ha planteado retos a nivel tecnológico y médico, ya que requiere no sólo varios años de estudio, sino también experiencia por parte de los médicos especialistas para examinar las imágenes y realizar un diagnóstico oportuno. Durante esta pandemia de COVID-19 muchos pacientes con esta patología han sufrido constantes cambios y la presión intraocular ha aumentado considerablemente, por lo que la detección temprana es de vital importancia, además de brindar un tratamiento adecuado y oportuno para que el paciente no pierda la visión en su totalidad y mitigar los efectos que el COVID-19 ha causado en estos pacientes. En este artículo se presentan las diferentes técnicas para el diagnóstico del glaucoma y los métodos de detección automática, así como el análisis del procesamiento de imágenes y los resultados obtenidos en la etapa de preprocesamiento, la caracterización de esta enfermedad según diferentes puntos de vista, también se presenta un análisis exhaustivo de cada uno de los métodos propuestos para el apoyo al diagnóstico médico, las características de cada uno de los clasificadores y datos de gran relevancia para futuros trabajos.

Título traducido de la contribución	Métodos para la detección automática de glaucoma y extracción de características mediante diferentes técnicas en la etapa de preprocesamiento en imágenes de fondo de ojo
Idioma original	Inglés estadounidense
DOI	https://doi.org/10.54941/ahfe1002691
Estado	Publicada - 31 jul. 2022
Evento	13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022) and the Affiliated Conferences - US Duración: 24 jul. 2022 → 28 jul. 2022 https://ahfe.org/

Conferencia

Conferencia	13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022) and the Affiliated Conferences
Período	24/07/22 → 28/07/22
Dirección de internet	https://ahfe.org/

Palabras clave

Fundus images
Glaucoma detection
Neural network
Support of medical diagnosis

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819A Salud Pública

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10.54941/ahfe1002691

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Pinos Velez, E. G., Cordero Mendieta, M. I., & Coronel Berrezueta, R. F. (2022). Methods for Automatic Glaucoma Detection and Feature Extraction by Different Techniques at the Pre-processing Stage in Fundus Images. Papel presentado en 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022) and the Affiliated Conferences. https://doi.org/10.54941/ahfe1002691

Pinos Velez, Eduardo Guillermo ; Cordero Mendieta, Maria Isabel ; Coronel Berrezueta, Roberto Francisco. / Methods for Automatic Glaucoma Detection and Feature Extraction by Different Techniques at the Pre-processing Stage in Fundus Images. Papel presentado en 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022) and the Affiliated Conferences.

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title = "Methods for Automatic Glaucoma Detection and Feature Extraction by Different Techniques at the Pre-processing Stage in Fundus Images",

abstract = "Glaucoma is a neurodegenerative, progressive and silent disease that affects the optic nerve, characterized by an increase in intraocular pressure causing irreversible damage to the optic nerve. The difficulty in early diagnosis of glaucoma has posed challenges at the technological and medical level, since it requires not only several years of study, but also experience on the part of medical specialists to examine the images and make a timely diagnosis. During this pandemic of COVID-19 many patients with this pathology have suffered constant changes and intraocular pressure has increased considerably, so early detection is of vital importance, in addition to providing appropriate and timely treatment so that the patient does not lose vision in its entirety and mitigate the effects that COVID-19 has caused in these patients. In this article we present the different techniques for the diagnosis of glaucoma and the automatic detection methods, as well as the analysis of image processing and the results obtained in the preprocessing stage, the characterization of this disease according to different points of view, we also present a thorough analysis of each of the methods proposed for the support of medical diagnosis, the characteristics of each of the classifiers and data of great relevance for future work.",

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Pinos Velez, EG, Cordero Mendieta, MI & Coronel Berrezueta, RF 2022, 'Methods for Automatic Glaucoma Detection and Feature Extraction by Different Techniques at the Pre-processing Stage in Fundus Images', Papel presentado en 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022) and the Affiliated Conferences, 24/07/22 - 28/07/22. https://doi.org/10.54941/ahfe1002691

Methods for Automatic Glaucoma Detection and Feature Extraction by Different Techniques at the Pre-processing Stage in Fundus Images. / Pinos Velez, Eduardo Guillermo; Cordero Mendieta, Maria Isabel; Coronel Berrezueta, Roberto Francisco.
2022. Papel presentado en 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022) and the Affiliated Conferences.

Producción científica: Contribución a una conferencia › Documento

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AU - Cordero Mendieta, Maria Isabel

AU - Coronel Berrezueta, Roberto Francisco

PY - 2022/7/31

Y1 - 2022/7/31

N2 - Glaucoma is a neurodegenerative, progressive and silent disease that affects the optic nerve, characterized by an increase in intraocular pressure causing irreversible damage to the optic nerve. The difficulty in early diagnosis of glaucoma has posed challenges at the technological and medical level, since it requires not only several years of study, but also experience on the part of medical specialists to examine the images and make a timely diagnosis. During this pandemic of COVID-19 many patients with this pathology have suffered constant changes and intraocular pressure has increased considerably, so early detection is of vital importance, in addition to providing appropriate and timely treatment so that the patient does not lose vision in its entirety and mitigate the effects that COVID-19 has caused in these patients. In this article we present the different techniques for the diagnosis of glaucoma and the automatic detection methods, as well as the analysis of image processing and the results obtained in the preprocessing stage, the characterization of this disease according to different points of view, we also present a thorough analysis of each of the methods proposed for the support of medical diagnosis, the characteristics of each of the classifiers and data of great relevance for future work.

AB - Glaucoma is a neurodegenerative, progressive and silent disease that affects the optic nerve, characterized by an increase in intraocular pressure causing irreversible damage to the optic nerve. The difficulty in early diagnosis of glaucoma has posed challenges at the technological and medical level, since it requires not only several years of study, but also experience on the part of medical specialists to examine the images and make a timely diagnosis. During this pandemic of COVID-19 many patients with this pathology have suffered constant changes and intraocular pressure has increased considerably, so early detection is of vital importance, in addition to providing appropriate and timely treatment so that the patient does not lose vision in its entirety and mitigate the effects that COVID-19 has caused in these patients. In this article we present the different techniques for the diagnosis of glaucoma and the automatic detection methods, as well as the analysis of image processing and the results obtained in the preprocessing stage, the characterization of this disease according to different points of view, we also present a thorough analysis of each of the methods proposed for the support of medical diagnosis, the characteristics of each of the classifiers and data of great relevance for future work.

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KW - Glaucoma detection

KW - Neural network

KW - Support of medical diagnosis

KW - Fundus images

KW - Glaucoma detection

KW - Neural network

KW - Support of medical diagnosis

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Y2 - 24 July 2022 through 28 July 2022

ER -

Methods for Automatic Glaucoma Detection and Feature Extraction by Different Techniques at the Pre-processing Stage in Fundus Images

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