TeleOphta: Machine learning and image processing methods for teleophthalmology

被引：304

作者：

Decenciere, E. ^{[1
]}

Cazuguel, G. ^{[4
,6
]}

Zhang, X. ^{[1
]}

Thibault, G. ^{[1
]}

Klein, J. -C. ^{[1
]}

Meyer, F. ^{[1
]}

Marcotegui, B. ^{[1
]}

Quellec, G. ^{[4
]}

Lamard, M. ^{[4
,7
]}

Danno, R. ^{[5
]}

Elie, D. ^{[5
]}

Massin, P. ^{[2
]}

Viktor, Z. ^{[2
]}

Erginay, A. ^{[2
]}

Lay, B. ^{[5
]}

Chabouis, A. ^{[3
]}

机构：

[1] MINES ParisTech, Ctr Math Morphol, Syst & Math Dept, F-77300 Fontainebleau, France

[2] Hop Lariboisiere, AP HP, Serv Ophtalmol, F-75475 Paris 10, France

[3] AP HP, Parcours Patients & Org Med Innovantes Telemed, Direct Polit Med, F-75184 Paris 04, France

[4] CHRU Morvan, Inserm UMR LaTIM 1101, F-29200 Brest, France

[5] ADCIS, F-14280 St Contest, France

[6] Telecom Bretagne, Inst Mines Telecom, ITI Dept, F-29200 Brest, France

[7] Univ Brest, Inserm UMR LaTIM 1101, SFR ScInBioS, F-29200 Brest, France

来源：

IRBM | 2013年 / 34卷 / 02期

关键词：

MICROANEURYSMS; RETRIEVAL;

D O I：

10.1016/j.irbm.2013.01.010

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

A complete prototype for the automatic detection of normal examinations on a teleophthalmology network for diabetic retinopathy screening is presented. The system combines pathological pattern mining methods, with specific lesion detection methods, to extract information from the images. This information, plus patient and other contextual data, is used by a classifier to compute an abnormality risk. Such a system should reduce the burden on readers on teleophthalmology networks. (C) 2013 Elsevier Masson SAS. All rights reserved.

引用

页码：196 / 203

页数：8

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