Access Restriction

Author Quellec, G. ♦ Lamard, M. ♦ Cochener, B. ♦ Droueche, Z. ♦ Lay, B. ♦ Chabouis, A. ♦ Roux, C. ♦ Cazuguel, G.
Sponsorship IEEE Eng. Medicine Biol. Soc.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2012
Language English
Subject Domain (in DDC) Technology ♦ Medicine & health ♦ Engineering & allied operations
Subject Keyword Retina ♦ Diabetes ♦ Image quality ♦ Algorithm design and analysis ♦ Retinopathy ♦ Training
Abstract In recent years, many image analysis algorithms have been presented to assist Diabetic Retinopathy (DR) screening. The goal was usually to detect healthy examination records automatically, in order to reduce the number of records that should be analyzed by retinal experts. In this paper, a novel application is presented: these algorithms are used to 1) discover image characteristics that sometimes cause an expert to disagree with his/her peers and 2) warn the expert whenever these characteristics are detected in an examination record. In a DR screening program, each examination record is only analyzed by one expert, therefore analyzing disagreements among experts is challenging. A statistical framework, based on Parzen-windowing and the Patrick-Fischer distance, is presented to solve this problem. Disagreements among eleven experts from the Ophdiat screening program were analyzed, using an archive of 25,702 examination records.
Description Author affiliation: Inserm, Brest, France (Quellec, G.; Lamard, M.; Cochener, B.; Droueche, Z.; Roux, C.; Cazuguel, G.) || ADCIS, St. Contest, France (Lay, B.) || Service d'Ophtalmologie, Hopital Lariboisiere - APHP, Paris, France (Chabouis, A.)
ISBN 9781424441198
ISSN 1557170X
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2012-08-28
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781457717871
Size (in Bytes) 1.65 MB
Page Count 4
Starting Page 5959
Ending Page 5962

Source: IEEE Xplore Digital Library