An Automatic Detection and Classification System of Five Stages for Hypertensive Retinopathy Using Semantic and Instance Segmentation in DenseNet Architecture.

Abbas, Qaisar; Qureshi, Imran; Ibrahim, Mostafa E A

Abbas, Qaisar; Qureshi, Imran; Ibrahim, Mostafa E A.

Afiliação

Abbas Q; College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia.
Qureshi I; Department of Computer Software Engineering, Military College of Signals, National University of Sciences and Technology (MCS-NUST), Islamabad 44000, Pakistan.
Ibrahim MEA; College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia.

Sensors (Basel) ; 21(20)2021 Oct 19.

Article em En | MEDLINE | ID: mdl-34696149

Assuntos

Aprendizado Profundo; Retinopatia Diabética; Retinopatia Hipertensiva; Fundo de Olho; Humanos; Retinopatia Hipertensiva/diagnóstico; Semântica

Palavras-chave

DenseNet architecture; deep-neural network; diabetic retinopathy; hypertensive retinopathy; loss function; perceptual-oriented color space; retinal fundus images; semantic and instance-based segmentation; transfer learning

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Retinopatia Diabética / Retinopatia Hipertensiva / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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