Vol. 1 No. 4 (2017)
Modeling and Artificial Intelligence in Ophthalmology
Modeling and Artificial Intelligence in Ophthalmology
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Vol. 1 No. 4 (2017)
Published July 7, 2017
https://doi.org/10.35119/maio.v1i4
Editorial
REVAMMAD JMO Special Edition
Andrew Hunter, Jens Christian Brings Jacobsen
4-5
https://doi.org/10.35119/maio.v1i4.56
PDF
Original Articles
Hemodynamics in the retinal vasculature during the progression of diabetic retinopathy
Francesco Calivá, Georgios Leontidis, Piotr Chudzik, Andrew Hunter, Luca Antiga, Bashir Al-Diri
6-15
https://doi.org/10.35119/maio.v1i4.41
PDF
FIRE: Fundus Image Registration dataset
Carlos Hernandez-Matas, Xenophon Zabulis, Areti Triantafyllou, Panagiota Anyfanti, Stella Douma, Antonis A Argyros
16-28
https://doi.org/10.35119/maio.v1i4.42
PDF
A shortest path approach to optic disc detection in retinal fundus images
Jeffrey Wigdahl, Pedro Guimaraes, Alfredo Ruggeri
29-42
https://doi.org/10.35119/maio.v1i4.43
PDF
Dynamical characteristics of microvascular networks with a myogenic response gradient
Anastasiia Neganova
43-61
https://doi.org/10.35119/maio.v1i4.45
PDF
Hemodynamic parameters and vessel tortuosity: an investigation with a mesenterial vascular network
Roberto Annunziata, Bettina Reglin, Axel Pries, Emanuele Trucco
62-68
https://doi.org/10.35119/maio.v1i4.46
PDF
A classification model for predicting diabetic retinopathy based on patient characteristics and biochemical measures
Evangelia Kotsiliti, Bashir Al-Diri, Andrew Hunter
69-85
https://doi.org/10.35119/maio.v1i4.47
PDF
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