Deep-learning classifier with ultrawide-field fundus ophthalmoscopy for detecting branch retinal vein occlusion | Zendy

Daisuke Nagasato | Zendy; Hitoshi Tabuchi | Zendy; Hideharu Ohsugi | Zendy; Hiroki Masumoto | Zendy; Hiroki Enno | Zendy; Naofumi Ishitobi | Zendy; Tomoaki Sonobe | Zendy; Masahiro Kameoka | Zendy; Masanori Niki | Zendy; Yoshinori Mitamura | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Deep-learning classifier with ultrawide-field fundus ophthalmoscopy for detecting branch retinal vein occlusion

Author(s) -

Daisuke Nagasato,

Hitoshi Tabuchi,

Hideharu Ohsugi,

Hiroki Masumoto,

Hiroki Enno,

Naofumi Ishitobi,

Tomoaki Sonobe,

Masahiro Kameoka,

Masanori Niki,

Yoshinori Mitamura

Publication year - 2019

Publication title -

international journal of ophthalmology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.634

H-Index - 29

eISSN - 2227-4898

pISSN - 2222-3959

DOI - 10.18240/ijo.2019.01.15

Subject(s) - medicine , branch retinal vein occlusion , fundus (uterus) , artificial intelligence , ophthalmology , support vector machine , retinal , macular edema , computer science

To investigate and compare the efficacy of two machine-learning technologies with deep-learning (DL) and support vector machine (SVM) for the detection of branch retinal vein occlusion (BRVO) using ultrawide-field fundus images.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research