Automated quality assessment of retinal fundus photos

International Journal of Computer Assisted Radiology and Surgery

Volumn 5, Issue 6, 2010, Pages 557-564

  Paulus, Jan ^a   Meier, Jörg ^a   Bock, Rüdiger ^a   Hornegger, Joachim ^a   Michelson, Georg ^a  

^a UNIVERSITY OF ERLANGEN NUREMBERG   (Germany)

Author keywords

Fundus image; Non reference image quality metric; Quality assessment; Retina

Indexed keywords

ACCURACY; ALGORITHM; ARTICLE; AUTOMATION; CLASSIFICATION; DIAGNOSTIC PROCEDURE; EYE FUNDUS; EYE PHOTOGRAPHY; IMAGE ANALYSIS; IMAGE QUALITY; MEDICAL ASSESSMENT; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; RELIABILITY; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE;

EID: 79251630763     PISSN: 18616410     EISSN: 18616429     Source Type: Journal    
DOI: 10.1007/s11548-010-0479-7     Document Type: Article

References (14)

1. MD Abràmoff M Niemeijer MS Suttorp-Schulten MA Viergever SR Russell B van Ginneken 2008 Evaluation of a system for automatic detection of diabetic retinopathy from color fundus photographs in a large population of patients with diabetes Diabetes Care 31 2 193 198 10.2337/dc07-1312 18024852 (Pubitemid 351213318)
2. R Bock J Meier LG Nyúl J Hornegger G Michelson 2010 Glaucoma risk index: automated glaucoma detection from color fundus images Med Image Anal 14 3 471 481 10.1016/j.media.2009.12.006 20117959
3. C Sinthanayothin JF Boyce TH Williamson HL Cook E Mensah S Lal D Usher 2002 Automated detection of diabetic retinopathy on digital fundus images Diabetic Med 19 2 105 112 1:STN:280:DC%2BD387jvVGlsg%3D%3D 10.1046/j.1464-5491. 2002.00613.x 11874425 (Pubitemid 34225223)
4. MD Abràmoff M Suttorp-Schulten 2005 screening for diabetic retinopathy in a primary care population: the eye check project Telemed e-Health 11 6 668 674 10.1089/tmj.2005.11.668 (Pubitemid 43227822)
5. AM Eskicioglu PS Fisher 1995 Quality measures and their performance IEEE Trans Commun 3 12 2959 2965 10.1109/26.477498
6. İ AvcIbaş B Sankur K Sayood 2002 Statistical evaluation of image quality measures J Electron Imaging 11 2 206 223 10.1117/1.1455011 (Pubitemid 34536986)
7. Z Wang AC Bovik L Lu 2002 Why is image quality assessment so difficult? IEEE Int Conf Acoust Speech Signal Process Proc 4 3313 3316
8. AD Fleming S Philip KA Goatman JA Olson PF Sharp 2006 Automated assessment of diabetic retinal image quality based on clarity and field definition Investig Ophthalmol Visual Sci 47 3 1120 1125 10.1167/iovs.05-1155 (Pubitemid 46768348)
9. Giancardo L, Abràmoff MD, Chaum E, Karnowski TP, Meriaudeau F, Tobin KW Jr (2008) Elliptical local vessel density: a fast and robust quality metric for retinal images, Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th annual international conference of the IEEE, pp 3534-3537
10. Lalonde M, Gagnony L, Boucher M-C (2001)Automatic visual quality assessment in optical fundus images. Proceedings of Vision Interface (VI 2001), pp 259-264
11. SC Lee Y Wang 1999 Automatic retinal image quality assessment and enhancement Proc SPIE 3661 1581 1590 10.1117/12.348562
12. M Niemeijer MD Abràmoff B Ginneken 2006 Image structure clustering for image quality verification of color retina images in diabetic retinopathy screening Med Image Anal 10 6 888 898 10.1016/j.media.2006.09.006 17138215 (Pubitemid 44815259)
13. RM van Haralick K Shanmugam I Dinstein 1973 Textural features for image classification IEEE Trans Syst Man Cybern 3 6 610 621 10.1109/TSMC.1973.4309314
14. Chang C-C, Lin C-J (2001) "LIBSVM": a library for support vector machines, http://www.csie.ntu.edu.tw/~cjlin/libsvm