Literature DB >> 16897222

Feasibility study on computer-aided screening for diabetic retinopathy.

Apichart Singalavanija1, Jirayuth Supokavej1, Parapan Bamroongsuk1, Chanjira Sinthanayothin2, Suthee Phoojaruenchanachai2, Viravud Kongbunkiat2.   

Abstract

PURPOSE: To conduct a feasibility study of computer-aided screening for diabetic retinopathy by developing a computerized program to automatically detect retinal changes from digital retinal images.
METHODS: The study was carried out in three steps. Step 1 was to collect baseline retinal image data of 600 eyes of normal subjects with normal fundi and data of 300 eyes of diabetic patients with diabetic retinopathy. All data were recorded by digital fundus camera. Step 2 was to analyse all retinal images for normal and abnormal features. By this method, the automated computerized screening program was developed. The program preprocesses colour retinal images and recognizes the main retinal components (optic disc, fovea, and blood vessels) and diabetic features such as exudates, haemorrhages, and microaneurysms. All of the accumulated information is interpreted as normal, abnormal, or unknown. Step 3 was to evaluate the sensitivity and specificity of the computerized screening program by testing the program on diabetic patients and comparing the program's results with the results of screening by retinal specialists.
RESULTS: Diabetic patients (182 patients, 336 eyes) were examined by retinal specialists; 221 eyes had a normal fundus and 115 eyes had nonproliferative diabetic retinopathy. Digital retinal images were taken of these 336 eyes and interpreted by the automated screening program. The program had a sensitivity and specificity of 74.8% and 82.7%, respectively.
CONCLUSIONS: The automated screening program was able to differentiate between the normal fundus and the diabetic retinopathy fundus. The program may be beneficial for use in screening for diabetic retinopathy. Further development of the program may provide higher sensitivity. Copyright (c) Japanese Ophthalmological Society 2006.

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Year:  2006        PMID: 16897222     DOI: 10.1007/s10384-005-0328-3

Source DB:  PubMed          Journal:  Jpn J Ophthalmol        ISSN: 0021-5155            Impact factor:   2.447


  30 in total

1.  National screening programme for diabetic retinopathy. Digital image may be better for screening.

Authors:  Colin Clements
Journal:  BMJ       Date:  2002-04-06

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Authors:  R P Phillips; T Spencer; P G Ross; P F Sharp; J V Forrester
Journal:  Eye (Lond)       Date:  1991       Impact factor: 3.775

3.  Comparison of diagnosis of early retinal lesions of diabetic retinopathy between a computer system and human experts.

Authors:  S C Lee; E T Lee; R M Kingsley; Y Wang; D Russell; R Klein; A Warn
Journal:  Arch Ophthalmol       Date:  2001-04

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Authors:  D R Owens; R L Gibbins; P A Lewis; S Wall; J C Allen; R Morton
Journal:  Diabet Med       Date:  1998-02       Impact factor: 4.359

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Authors:  J A Pugh; J M Jacobson; W A Van Heuven; J A Watters; M R Tuley; D R Lairson; R J Lorimor; A S Kapadia; R Velez
Journal:  Diabetes Care       Date:  1993-06       Impact factor: 19.112

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Journal:  Invest Ophthalmol Vis Sci       Date:  1981-07       Impact factor: 4.799

7.  Evaluation of a new non-mydriatic digital camera for detection of diabetic retinopathy.

Authors:  P Massin; A Erginay; A Ben Mehidi; E Vicaut; G Quentel; Z Victor; M Marre; P J Guillausseau; A Gaudric
Journal:  Diabet Med       Date:  2003-08       Impact factor: 4.359

8.  Diabetic retinopathy as detected using ophthalmoscopy, a nonmydriatic camera and a standard fundus camera.

Authors:  R Klein; B E Klein; M W Neider; L D Hubbard; S M Meuer; R J Brothers
Journal:  Ophthalmology       Date:  1985-04       Impact factor: 12.079

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Authors:  J C Javitt; J K Canner; A Sommer
Journal:  Ophthalmology       Date:  1989-02       Impact factor: 12.079

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Authors:  J C Javitt; L P Aiello; L J Bassi; Y P Chiang; J K Canner
Journal:  Ophthalmology       Date:  1991-10       Impact factor: 12.079

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  3 in total

1.  [Fundus screening by medical technicians].

Authors:  F Schütt; T Bruckner; K Schäfer; D Lehnhoff; G Rudofsky; C Kasperk; P Nawroth; G U Auffarth
Journal:  Ophthalmologe       Date:  2013-02       Impact factor: 1.059

Review 2.  Algorithms for the automated detection of diabetic retinopathy using digital fundus images: a review.

Authors:  Oliver Faust; Rajendra Acharya U; E Y K Ng; Kwan-Hoong Ng; Jasjit S Suri
Journal:  J Med Syst       Date:  2010-04-06       Impact factor: 4.460

Review 3.  Automated detection of diabetic retinopathy in retinal images.

Authors:  Carmen Valverde; Maria Garcia; Roberto Hornero; Maria I Lopez-Galvez
Journal:  Indian J Ophthalmol       Date:  2016-01       Impact factor: 1.848

  3 in total

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