Literature DB >> 1547965

Automated detection and quantification of microaneurysms in fluorescein angiograms.

T Spencer1, R P Phillips, P F Sharp, J V Forrester.   

Abstract

Fluorescein angiograms from diabetics were digitised for analysis using digital image-processing techniques. Computer algorithms were written to detect and count microaneurysms present in the images. The accuracy, speed and reproducibility of the technique were assessed and compared with those of manual counts made by clinicians from both digitised and analogue images. Free-response ROC (receiver operating characteristic) curves were used to assess the performance of both the clinicians and the computer by comparing the results with "gold standards" compiled from prints of the original fluorescein angiograms. The computer performed as well as the clinicians when the latter were analysing the digitised images (512 x 512 pixel resolution), but only when one image was acquired at 4 times this resolution did the computer's performance match that of the clinicians analysing the analogue image. The automated technique was more reproducible than the manual method.

Entities:  

Mesh:

Year:  1992        PMID: 1547965     DOI: 10.1007/bf00166760

Source DB:  PubMed          Journal:  Graefes Arch Clin Exp Ophthalmol        ISSN: 0721-832X            Impact factor:   3.117


  14 in total

Review 1.  Electro-optic fundus imaging.

Authors:  E Peli
Journal:  Surv Ophthalmol       Date:  1989 Sep-Oct       Impact factor: 6.048

2.  Detection of blood vessels in retinal images using two-dimensional matched filters.

Authors:  S Chaudhuri; S Chatterjee; N Katz; M Nelson; M Goldbaum
Journal:  IEEE Trans Med Imaging       Date:  1989       Impact factor: 10.048

Review 3.  ROC methodology in radiologic imaging.

Authors:  C E Metz
Journal:  Invest Radiol       Date:  1986-09       Impact factor: 6.016

4.  Image analysis of fundus photographs. The detection and measurement of exudates associated with diabetic retinopathy.

Authors:  N P Ward; S Tomlinson; C J Taylor
Journal:  Ophthalmology       Date:  1989-01       Impact factor: 12.079

5.  Use of directly acquired digital fundus and fluorescein angiographic images in the diagnosis of retinal disease.

Authors:  T R Friberg; P G Rehkopf; J W Warnicki; A W Eller
Journal:  Retina       Date:  1987       Impact factor: 4.256

6.  Automatic geometrical registration of fluorescein retinal angiograms.

Authors:  R Jagoe; C I Blauth; P L Smith; J V Arnold; K Taylor; R Wootton
Journal:  Comput Biomed Res       Date:  1990-10

7.  Automatic detection of microaneurysms in diabetic fluorescein angiography.

Authors:  C E Baudoin; B J Lay; J C Klein
Journal:  Rev Epidemiol Sante Publique       Date:  1984       Impact factor: 1.019

8.  Quantitative evaluation of fluorescein angiograms: microaneurysm counts.

Authors:  C Baudoin; F Maneschi; G Quentel; G Soubrane; T Hayes; G Jones; G Coscas; E M Kohner
Journal:  Diabetes       Date:  1983-05       Impact factor: 9.461

9.  The relationship of retinal microaneurysm counts to the 4-year progression of diabetic retinopathy.

Authors:  R Klein; S M Meuer; S E Moss; B E Klein
Journal:  Arch Ophthalmol       Date:  1989-12

10.  Does microaneurysm count reflect severity of early diabetic retinopathy?

Authors:  E M Kohner; M Sleightholm
Journal:  Ophthalmology       Date:  1986-05       Impact factor: 12.079

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  12 in total

1.  Automated localisation of the optic disc, fovea, and retinal blood vessels from digital colour fundus images.

Authors:  C Sinthanayothin; J F Boyce; H L Cook; T H Williamson
Journal:  Br J Ophthalmol       Date:  1999-08       Impact factor: 4.638

2.  Automated, real time extraction of fundus images from slit lamp fundus biomicroscope video image sequences.

Authors:  B D Madjarov; J W Berger
Journal:  Br J Ophthalmol       Date:  2000-06       Impact factor: 4.638

3.  Validating retinal fundus image analysis algorithms: issues and a proposal.

Authors:  Emanuele Trucco; Alfredo Ruggeri; Thomas Karnowski; Luca Giancardo; Edward Chaum; Jean Pierre Hubschman; Bashir Al-Diri; Carol Y Cheung; Damon Wong; Michael Abràmoff; Gilbert Lim; Dinesh Kumar; Philippe Burlina; Neil M Bressler; Herbert F Jelinek; Fabrice Meriaudeau; Gwénolé Quellec; Tom Macgillivray; Bal Dhillon
Journal:  Invest Ophthalmol Vis Sci       Date:  2013-05-01       Impact factor: 4.799

4.  Fully automatic segmentation of fluorescein leakage in subjects with diabetic macular edema.

Authors:  Hossein Rabbani; Michael J Allingham; Priyatham S Mettu; Scott W Cousins; Sina Farsiu
Journal:  Invest Ophthalmol Vis Sci       Date:  2015-01-29       Impact factor: 4.799

5.  Automated detection and quantification of retinal exudates.

Authors:  R Phillips; J Forrester; P Sharp
Journal:  Graefes Arch Clin Exp Ophthalmol       Date:  1993-02       Impact factor: 3.117

6.  Characterisation of the neovascularisation process in diabetic retinopathy by means of fractal geometry: diagnostic implications.

Authors:  A Daxer
Journal:  Graefes Arch Clin Exp Ophthalmol       Date:  1993-12       Impact factor: 3.117

7.  Clinical investigation of an infrared digital scanning laser ophthalmoscope.

Authors:  A Manivannan; J N Kirkpatrick; P F Sharp; J V Forrester
Journal:  Br J Ophthalmol       Date:  1994-02       Impact factor: 4.638

8.  Automatic detection of diabetic retinopathy using an artificial neural network: a screening tool.

Authors:  G G Gardner; D Keating; T H Williamson; A T Elliott
Journal:  Br J Ophthalmol       Date:  1996-11       Impact factor: 4.638

9.  Automated identification of diabetic retinopathy stages using digital fundus images.

Authors:  Jagadish Nayak; P Subbanna Bhat; Rajendra Acharya; C M Lim; Manjunath Kagathi
Journal:  J Med Syst       Date:  2008-04       Impact factor: 4.460

Review 10.  Automated retinal image analysis for diabetic retinopathy in telemedicine.

Authors:  Dawn A Sim; Pearse A Keane; Adnan Tufail; Catherine A Egan; Lloyd Paul Aiello; Paolo S Silva
Journal:  Curr Diab Rep       Date:  2015-03       Impact factor: 5.430

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