Automated Segmentation of the Optic Disc from Stereo Color Photographs Using Physiologically Plausible Features | Zendy

Michael D. Abràmoff | Zendy; Wallace L.M. Alward | Zendy; Emily C. Greenlee | Zendy; Lesya Shuba | Zendy; Chan Yun Kim | Zendy; John H. Fingert | Zendy; Young H. Kwon | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Automated Segmentation of the Optic Disc from Stereo Color Photographs Using Physiologically Plausible Features

Author(s) -

Michael D. Abràmoff,

Wallace L.M. Alward,

Emily C. Greenlee,

Lesya Shuba,

Chan Yun Kim,

John H. Fingert,

Young H. Kwon

Publication year - 2007

Publication title -

investigative ophthalmology and visual science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.935

H-Index - 218

eISSN - 1552-5783

pISSN - 0146-0404

DOI - 10.1167/iovs.06-1081

Subject(s) - optic disc , artificial intelligence , glaucoma , pixel , segmentation , computer vision , feature (linguistics) , fundus (uterus) , computer science , stereopsis , mathematics , ophthalmology , medicine , linguistics , philosophy

To evaluate a novel automated segmentation algorithm for cup-to-disc segmentation from stereo color photographs of patients with glaucoma for the measurement of glaucoma progression.

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