Computer-assisted microaneurysm turnover in the early stages of diabetic retinopathy

Ophthalmologica

Volumn 223, Issue 5, 2009, Pages 284-291

  Bernardes, Rui ^a,b   Nunes, Sandrina ^a   Pereira, Ivânia ^a   Torrent, Teresa ^a   Rosa, Andreia ^a,d   Coelho, Dalila ^d   Cunha Vaz, José ^a,c,d  

^a ASSOCIATION FOR INNOVATION AND BIOMEDICAL RESEARCH ON LIGHT AND IMAGE AIBILI   (Portugal)

^b UNIVERSITY OF COIMBRA   (Portugal)

^c UNIVERSITY OF COIMBRA   (Portugal)

^d CENTRO HOSPITALAR E UNIVERSITÁRIO DE COIMBRA   (Portugal)

Author keywords

Color fundus photography; Diabetic retinopathy; Image co registration; Microaneurysm count; Microaneurysm disappearance rate; Microaneurysm formation rate; Microaneurysm turnover

Indexed keywords

ADULT; AGED; ARTICLE; CLINICAL ARTICLE; CLINICAL ASSESSMENT; CLINICAL TRIAL; COLOR FUNDUS PHOTOGRAPHY; DIABETIC RETINOPATHY; EYE PHOTOGRAPHY; FEMALE; FLUORESCENCE ANGIOGRAPHY; HUMAN; MALE; MICROANEURYSM; MICROANEURYSM TURNOVER; NON INSULIN DEPENDENT DIABETES MELLITUS; NON INVASIVE PROCEDURE; RELIABILITY;

ADULT; AGED; ANEURYSM; DIABETES MELLITUS, TYPE 2; DIABETIC RETINOPATHY; DIAGNOSTIC TECHNIQUES, OPHTHALMOLOGICAL; DISEASE PROGRESSION; FEMALE; FLUORESCEIN ANGIOGRAPHY; FOLLOW-UP STUDIES; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MACULAR EDEMA; MALE; MIDDLE AGED; OBSERVER VARIATION; PHOTOGRAPHY; REPRODUCIBILITY OF RESULTS; RETINAL VESSELS; RETROSPECTIVE STUDIES;

EID: 64549164464     PISSN: 00303755     EISSN: None     Source Type: Journal    
DOI: 10.1159/000213638     Document Type: Article

References (24)

1. Cunha-Vaz J: Characterization and relevance of different diabetic retinopathy phenotypes. Dev Ophthalmol 2007; 39: 13-30.
2. Kohner EM, Stratton IM, Aldington SJ, Turner RC, Matthews DR: Microaneurysms in the development of diabetic retinopathy (UKPDS 42). UK Prospective Diabetes Study Group. Diabetologia 1999; 42: 1107-1112.
3. Hove MN, Kristensen JK, Lauritzen T, Bek T: The relationships between risk factors and the distribution of retinopathy lesions in type 2 diabetes. Acta Ophthalmol Scand 2006; 84: 619-623.
4. Klein R, Klein B, Moss SE, Cruickshanks KJ: The Wisconsin epidemiologic study of diabetic retinopathy. XV. The long-term incidence of macular edema. Ophthalmology 1995; 102: 7-16.
5. Hellstedt T, Immonen I: Disappearance and formation rates of microaneurysms in early diabetic retinopathy. Br J Ophthalmol 1996; 80: 135-139.
6. Kohner EM: Microvascular disease: what does the UKPDS tell us about diabetic reti-nopathy? Diabet Med 2008; 25(suppl 2):20-24.
7. Frame AJ, Undrill PE, Cree MJ, Olson JA, McHardy KC, Sharp PF, Forrester JV: A comparison of computer based classification methods applied to the detection of micro-aneurysms in ophthalmic fluorescein angio-grams. Comput Biol Med 1998; 28: 225-238.
8. Ege BM, Hejlesen OK, Larsen OV, Møller K, Jennings B, Kerr D, Cavan DA: Screening for diabetic retinopathy using computer based image analysis and statistical classification. Comput Methods Programs Biomed 2000; 62: 165-175.
9. Teng T, Lefley M, Claremont D: Progress towards automated diabetic ocular screening: a review of image analysis and intelligent systems for diabetic retinopathy. Med Biol Eng Comput 2002; 40: 2-13.
10. Goatman KA, Cree MJ, Olson JA, Forrester JV, Sharp PF: Automated measurement of microaneurysm turnover. Invest Ophthal-mol Vis Sci 2003; 44: 5335-5341.
11. Quellec G, Lamard M, Josselin PM, Cazu-guel G, Cochener B, Roux C: Optimal wave-let transform for the detection of microaneu-rysms in retina photographs. IEEE Trans Med Imaging 2008; 27: 1230-1241.
12. Ferreira J, Bernardes R, Baptista P, Cunha-Vaz J: Earmarking retinal changes in a sequence of digital color fundus photographs. 3rd Eur Med Biol Eng Conf, Prague, IFMBE Proc 2005, vol 11.
13. Petrou M, Bosdogianni P: Image Processing: The Fundamentals. Chichester, John Wiley & Sons, 1999.
14. Foracchia M, Grisan E, Ruggeri A: Luminosity and contrast normalization in retinal images. Med Image Anal 2005; 9: 179-190.
15. Sinthanayothin C, Boyce J, Cook H, Williamson T: Automated localisation of the optic disc, fovea, and retinal blood vessels from digital colour fundus images. Br J Ophthal-mol 1999; 83: 902-910.
16. Tek H, Comaniciu D, Williams J: Vessel detection by mean shift based ray propagation. IEEE Workshop Math Methods Biomed Image Analysis, 2001, pp 228-235.
17. Matsopoulos G, Asvestas P, Mouravliansky N, Delibasis K: Multimodal registration of retinal images using self organizing maps. IEEE Trans Med Imaging 2004; 23: 1557-1563.
18. Bernardes R, Baptista P, Dias J, Cunha-Vaz J: Multimodal functional and morphological nonrigid image registration. IEEE International Conference on Image Processing 2005; 1: 1133-1136.
19. Pearson J, Hines D, Golosman S, Kuglin C: Video-rate image correlation processor. Proceedings of SPIE, 1977, vol 119, pp 197-205.
20. Rangarajan L, Chui H, Bookstein F: The soft-assign procrustes matching algorithm; in Duncan J, Gindi G (eds): Information Processing in Medical Imaging. Heidelberg, Springer, 1997, pp 29-42.
21. Fleiss JL: Design and Analysis of Clinical Experiments. New York, John Wiley & Sons, 1986.
22. Landis JR, Koch GG: The measurement of observer agreement for categorical data. Biometrics 1977; 33: 159-174.
23. Lobo C, Bernardes R, Figueira JP, de Abreu JR, Cunha-Vaz JG: Three-year follow-up of blood-retinal barrier and retinal thickness alterations in patients with type 2 diabetes mellitus and mild nonproliferative diabetic retinopathy. Arch Ophthalmol 2004; 122: 211-217.
24. Csaky KG, Richman EA, Ferris FL: Report from the NEI/FDA Ophthalmic Clinical Trial Design and Endpoints Symposium. Invest Ophthalmol Vis Sci 2008; 49: 479-489.