Real-time diabetic retinopathy patient screening using multiscale AM-FM methods

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n this paper we present a robust and improved system for diabetic retinopathy (DR) screening. The goal of the system is to automatically screen out digital fundus photographs of diabetic patients who do not present signs of DR. This work is motivated by the large amount of diabetics in the world who...

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Detalles Bibliográficos
Autores: Murray, Victor, Agurto, Carla, Barriga, Simon
Formato: artículo
Fecha de Publicación:2012
Institución:Universidad de Ingeniería y tecnología
Repositorio:UTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.utec.edu.pe:20.500.12815/39
Enlace del recurso:https://hdl.handle.net/20.500.12815/39
https://doi.org/10.1109/ICIP.2012.6466912
Nivel de acceso:acceso abierto
Materia:Diabetes
Training
Retinopathy
Testing
Retina
Robustness
Loading
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dc.title.es_PE.fl_str_mv Real-time diabetic retinopathy patient screening using multiscale AM-FM methods
title Real-time diabetic retinopathy patient screening using multiscale AM-FM methods
spellingShingle Real-time diabetic retinopathy patient screening using multiscale AM-FM methods
Murray, Victor
Diabetes
Training
Retinopathy
Testing
Retina
Robustness
Loading
title_short Real-time diabetic retinopathy patient screening using multiscale AM-FM methods
title_full Real-time diabetic retinopathy patient screening using multiscale AM-FM methods
title_fullStr Real-time diabetic retinopathy patient screening using multiscale AM-FM methods
title_full_unstemmed Real-time diabetic retinopathy patient screening using multiscale AM-FM methods
title_sort Real-time diabetic retinopathy patient screening using multiscale AM-FM methods
author Murray, Victor
author_facet Murray, Victor
Agurto, Carla
Barriga, Simon
author_role author
author2 Agurto, Carla
Barriga, Simon
author2_role author
author
dc.contributor.author.fl_str_mv Murray, Victor
Agurto, Carla
Barriga, Simon
dc.subject.es_PE.fl_str_mv Diabetes
Training
Retinopathy
Testing
Retina
Robustness
Loading
topic Diabetes
Training
Retinopathy
Testing
Retina
Robustness
Loading
description n this paper we present a robust and improved system for diabetic retinopathy (DR) screening. The goal of the system is to automatically screen out digital fundus photographs of diabetic patients who do not present signs of DR. This work is motivated by the large amount of diabetics in the world who do not receive their recommended eye exams, leading to widespread blindness as a complication of diabetes. The system is based on multiscale amplitude-modulation frequency-modulation (AM-FM) methods for feature extraction, and uses supervised and unsupervised methods to produce its final output, namely, a normal or abnormal grade. The most time-consuming processing routines of the system are implemented in C using a compute unified device architecture (CUDA) to produce results in real-time. The system was tested using 776 images from 388 patients (one macula-centered image from each eye). During the training phase of the system, the data was divided in 70% for training and 30% for testing. The system was tested using 20 random training/testing distributions, obtaining an average sensitivity of 89% and specificity of 59%. Analysis of sight-threatening conditions resulted in a sensitivity of 98% for these types of cases.
publishDate 2012
dc.date.accessioned.none.fl_str_mv 2017-11-07T05:35:18Z
dc.date.available.none.fl_str_mv 2017-11-07T05:35:18Z
dc.date.issued.fl_str_mv 2012-10
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dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12815/39
dc.identifier.doi.es_PE.fl_str_mv https://doi.org/10.1109/ICIP.2012.6466912
dc.identifier.journal.es_PE.fl_str_mv 2012 19th IEEE International Conference on Image Processing
url https://hdl.handle.net/20.500.12815/39
https://doi.org/10.1109/ICIP.2012.6466912
identifier_str_mv 2012 19th IEEE International Conference on Image Processing
dc.language.iso.es_PE.fl_str_mv eng
language eng
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dc.format.es_PE.fl_str_mv application/pdf
dc.publisher.es_PE.fl_str_mv Institute of Electrical and Electronics Engineers
dc.source.es_PE.fl_str_mv Repositorio Institucional UTEC
Universidad de Ingeniería y Tecnología - UTEC
dc.source.none.fl_str_mv reponame:UTEC-Institucional
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spelling Murray, VictorAgurto, CarlaBarriga, Simon2017-11-07T05:35:18Z2017-11-07T05:35:18Z2012-10https://hdl.handle.net/20.500.12815/39https://doi.org/10.1109/ICIP.2012.64669122012 19th IEEE International Conference on Image Processingn this paper we present a robust and improved system for diabetic retinopathy (DR) screening. The goal of the system is to automatically screen out digital fundus photographs of diabetic patients who do not present signs of DR. This work is motivated by the large amount of diabetics in the world who do not receive their recommended eye exams, leading to widespread blindness as a complication of diabetes. The system is based on multiscale amplitude-modulation frequency-modulation (AM-FM) methods for feature extraction, and uses supervised and unsupervised methods to produce its final output, namely, a normal or abnormal grade. The most time-consuming processing routines of the system are implemented in C using a compute unified device architecture (CUDA) to produce results in real-time. The system was tested using 776 images from 388 patients (one macula-centered image from each eye). During the training phase of the system, the data was divided in 70% for training and 30% for testing. The system was tested using 20 random training/testing distributions, obtaining an average sensitivity of 89% and specificity of 59%. 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