Automated Diagnosis of Diabetic Retinopathy Using Deep Learning: On the Search of Segmented Retinal Blood Vessel Images for Better Performance.

Khan, Mohammad B; Ahmad, Mohiuddin; Yaakob, Shamshul B; Shahrior, Rahat; Rashid, Mohd A; Higa, Hiroki

Khan, Mohammad B; Ahmad, Mohiuddin; Yaakob, Shamshul B; Shahrior, Rahat; Rashid, Mohd A; Higa, Hiroki.

Afiliação

Khan MB; Department of Biomedical Engineering, Khulna University of Engineering and Technology, Khulna 9203, Bangladesh.
Ahmad M; Department of Electrical and Electronic Engineering, Khulna Engineering and Technology, Khulna 9203, Bangladesh.
Yaakob SB; Faculty of Electrical Engineering and Technology, Universiti Malaysia Perlis, Arau 02600, Malaysia.
Shahrior R; Department of Biomedical Engineering, Khulna University of Engineering and Technology, Khulna 9203, Bangladesh.
Rashid MA; Department of EEE, Noakhali Science and Technology University, Noakhali 3814, Bangladesh.
Higa H; Department of Electrical and Systems Engineering, University of the Ryukyus, Okinawa 903-0129, Japan.

Bioengineering (Basel) ; 10(4)2023 Mar 26.

Article em En | MEDLINE | ID: mdl-37106599

Palavras-chave

convolutional neural networks; deep learning; diabetic retinopathy; retinal blood vessels; segmentation

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Guideline / Screening_studies Idioma: En Revista: Bioengineering (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Bangladesh

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