Semi-automated detection of the foveal avascular zone in fluorescein angiograms in diabetes mellitus

Clinical and Experimental Ophthalmology

Volumn 34, Issue 2, 2006, Pages 119-123

  Conrath, John ^a,b   Valat, Olivier ^b   Giorgi, Roch ^b   Adel, Mouloud ^b   Raccah, Denis ^b   Meyer, Franck ^a,b   Ridings, Bernard ^a  

^a TIMONE HOSPITAL   (France)

^b LAVERAN MILITARY TEACHING HOSPITAL   (France)

Author keywords

Diabetic retinopathy; Fluorescein angiography; Foveal avascular zone; Region growing; Semi automated detection

Indexed keywords

ALGORITHM; ARTICLE; AUTOMATION; CLINICAL ARTICLE; COMPUTER PROGRAM; CONTROLLED STUDY; CORRELATION COEFFICIENT; DIABETES MELLITUS; DIABETIC RETINOPATHY; FEMALE; FLUORESCENCE ANGIOGRAPHY; HUMAN; IMAGE ANALYSIS; IMAGE QUALITY; MALE; RETINA BLOOD VESSEL OCCLUSION; RETINA FOVEA;

ALGORITHMS; CAPILLARIES; DIABETES COMPLICATIONS; DIABETIC RETINOPATHY; FEMALE; FLUORESCEIN ANGIOGRAPHY; FOVEA CENTRALIS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MALE; REGIONAL BLOOD FLOW; RETINAL VESSELS;

EID: 33644815574     PISSN: 14426404     EISSN: 14429071     Source Type: Journal    
DOI: 10.1111/j.1442-9071.2006.01138.x     Document Type: Article

References (14)

1. Bresnick GH, Condit R, Syrjala S, Palta M, Groo A, Korth K. Abnormalities of the foveal avascular zone in diabetic retinopathy. Arch Ophthalmol 1984; 102: 1286-93.
2. Arend O, Wolf S, Jung F, et al. Retinal microcirculation in patients with diabetes mellitus: Dynamic and morphological analysis of perfoveal capillary network. Br J Ophthalmol 1991; 75: 514-18.
3. Conrath J, Giorgi R, Raccah D, Ridings B. Foveal avascular zone in diabetic retinopathy: Quantitative versus qualitative assessment. Eye 10.1038/sj.eye.6704456.
4. Mansour AM, Schachat A, Bodiford G, Haymond R. Foveal avascular zone in diabetes mellitus. Retina 1993; 13: 125-8.
5. Spencer T, Phillips RP, Sharp PF, Forrester JV. Automated detection and quantification of microaneurysms in fluorescein angiograms. Graefes Arch Clin Exp Ophthalmol 1992; 230: 36-41.
6. Frame AJ, Undrill PE, Cree MJ et al. A comparison of computer based classification methods applied to the detection of microaneurysms in ophthalmic fluorescein angiograms. Comput Biol Med 1998; 28: 225-38.
7. Larsen M, Godt J, Larsen N et al. Automated detection of fundus photographic red lesions in diabetic retinopathy. Invest Ophthalmol Vis Sci 2003; 44: 761-6.
8. Gardner GG, Keating D, Williamson TH, Elliott AT. Automatic detection of diabetic retinopathy using an artificial neural network: A screening tool. Br J Ophthalmol 1996; 80: 940-4.
9. Walter T, Klein JC, Massin P, Erginay A. A contribution of image processing to the diagnosis of diabetic retinopathy - detection of exudates in color fundus images of the human retina. IEEE Trans Med Imaging 2002; 21: 1236-43.
10. Kozousek V, Shijiang S, Gregson P, Scott RC. Automated detection and quantification of venous beading using Fourier analysis. Can J Ophthalmol 1992; 27: 288-94.
11. Meunier I, Mimoun G, Bunel P, Quentel G, Soubrane G, Coscas G. Automated quantification of diabetic macular nonperfusion by digitized angiography. Invest Ophthalmol Vis Sci 1994; 35: 1595.
12. Ballerini L. Genetic snakes for medical images segmentation. In: Preteux F, Davidson JL, Dougherty ER, eds. Mathematical Modeling and Estimation Techniques in Computer Vision, Vol. 3457: Proc SPIE. San Diego, CA: SPIE Press, 1998; 284-95.
13. Ibanez MV, Simo A. Bayesian detection of the fovea in eye fundus angiographies. Pattern Recogn Lett 1999; 20: 229-40.
14. Sander B, Larsen M, Engler C, Lund-Andersen H, Parving HH. Early changes in diabetic retinopathy: Capillary loss and bloodretina barrier permeability in relation to metabolic control. Acta Ophthalmologica 1994; 72: 553-9.