Go to the content. | Move to the navigation | Go to the site search | Go to the menu | Contacts | Accessibility

| Create Account

De Luca, Massimo (2008) New techniques for the processing and analysis of retinal images in diagnostic ophtalmology. [Ph.D. thesis]

Full text disponibile come:

Documento PDF

Abstract (english)

This thesis deals with the automatic analysis of color fundus images and with its application to diagnostic ophthalmology.
Diabetes is a growing epidemia in the world, due to population growth, aging, urbanization and increasing prevalence of obesity and physical inactivity, so diabetic retinopathy has an ever increasing importance as a cause of blindness. Also hypertension affects the microcirculation and hypertensive retinopathy is one of the consequences of such damage.
In this thesis new algorithms to help ophthalmologist's diagnosis and to be used in automated systems for retinopathy screening will be presented .

Statistiche Download - Aggiungi a RefWorks
EPrint type:Ph.D. thesis
Tutor:Ruggeri, Alfredo
Ph.D. course:Ciclo 20 > Scuole per il 20simo ciclo > INGEGNERIA DELL'INFORMAZIONE > BIOINGEGNERIA
Data di deposito della tesi:January 2008
Anno di Pubblicazione:January 2008
Key Words:retinopathy medical imaging cad
Settori scientifico-disciplinari MIUR:Area 09 - Ingegneria industriale e dell'informazione > ING-INF/06 Bioingegneria elettronica e informatica
Struttura di riferimento:Dipartimenti > Dipartimento di Ingegneria dell'Informazione
Codice ID:443
Depositato il:30 Sep 2008
Simple Metadata
Full Metadata
EndNote Format


I riferimenti della bibliografia possono essere cercati con Cerca la citazione di AIRE, copiando il titolo dell'articolo (o del libro) e la rivista (se presente) nei campi appositi di "Cerca la Citazione di AIRE".
Le url contenute in alcuni riferimenti sono raggiungibili cliccando sul link alla fine della citazione (Vai!) e tramite Google (Ricerca con Google). Il risultato dipende dalla formattazione della citazione.

[1] L. G. Brown, “A survey of image registration techniques,” ACMComput. Surv., vol. 24, pp. 325–376, Dec. 1992. Cerca con Google

[2] B. Zitova and J. Flusser, “Image registration methods: A survey,” Image Vision Comput., vol. 21, pp. 977–1000, 2003. Cerca con Google

[3] P. A. van den Elsen, E. D. Pol, and M. A. Viergever, “Medical image matching—A review with classification,” IEEE Eng. Med. Biol. Mag., vol. 12, no. 1, pp. 26–39, Mar. 1993. Cerca con Google

[4] J. B. A. Maintz and M. A. Viegever, “A survey of medical image registration,” in Medical Image Analysis. Oxford, U.K.: Oxford Univ. Press, 1998. Cerca con Google

[5] G. K. Matsopoulos, N. A. Mouravliansky, K. K. Delibasis, and K. S. Nikita, “Automatic retinal image registration scheme using global optimization techniques,” IEEE Trans. Inf. Technol. Biomed., vol. 3, no. 1, pp. 47–60, Mar. 1999. Cerca con Google

[6] N. Ritter, R. Owens, J. Cooper, R. H. Eikelboom, and P. P. V. Saarloos, “Registration of stereo and temporal images of the retina,” IEEE Trans. Med. Imag., vol. 18, no. 5, pp. 404–418, May 1999. Cerca con Google

[7] E. De Castro and C. Morandi "Registration of Translated and Rotated Images Using Finite Fourier Transforms", IEEE Transactions on pattern analysis and machine intelligence, Sept. 1987 Cerca con Google

[8] F.Zana, J.Klein. A multimodal registration algorithm of eye fundus images using vessels detection and hough transform. IEEE Transactions on Medical Imaging, 18(5):419-428,May 1999. Cerca con Google

[9] J.Domingo,G.Ayala,A.Simò,E.de Ves.Irregular motion recovery in fluorescin angiograms.pattern recognition letters,18:805-821,1997. Cerca con Google

[10] C.D. Kuglin and D.C. Hines, “The phase correlation image alignment method” in Proc. 1975 Int. Conf. Cybernetics and Society, Sept.1975,pp. 163-165. Cerca con Google

[11] A.Can, C.Stewart,B.Roysam,L.Tanenbaum.”A featurefased, robust,hierarchical algorithm for registering pairs of images of the curved human retina.IEEE transactions on pattern analysis and machine learning,vol.24, n.3, march 2002 Cerca con Google

[12] L. D. Hubbard, R. J. Brothers, W. N. King, L. X. Clegg, R. Klein, L.S. Cooper, A. R. Sharrett, M. D. Davis, and J. Cai, “Methods for evaluation of retinal microvascular abnormalities associated with hypertension/sclerosis in the atherosclerosis risk in communities study,” Ophthalmology,vol. 106, pp. 2269–2280, Dec. 1999. Cerca con Google

[13] M. Foracchia, E. Grisan, A. Ruggeri, Detection of optic disc in retinal images by means of a geometrical model of vessel structure, IEEE Trans. Med. Imaging 23 (10) (2004) 1189–1195. Cerca con Google

[14] C. Sinthanayothin, J. F. Boyce, H. L. Cook, and T. H.Williamson, “Automated localisation of the optic disc, fovea and retinal blood vessels from digital colour fundus images,” British Journal of Ophtalmology, vol. 83, pp. 231–238, August 1999. Cerca con Google

[15] S. Tamura and Y. Okamoto, “Zero-crossing interval correction in tracing eye-fundus blood vessels,” Pattern Recognition, vol. 21, no. 3, pp. 227– 233, 1988. Cerca con Google

[16] T. Walter and J.-C. Klein, “Segmentation of color fundus images of the human retina: Detection of the optic disc and the vascular tree using morphological techniques,” proc. Second International Symposium on Medical Data Analysis (ISMDA 2001), pp. 282–287, Cerca con Google

October 2001. Cerca con Google

[17] H. Li, O. Chutatape, Automatic location of optic disk in retinal images, in: Proceedings of the International Conference on Image Processing, vol. 2, October 2001, pp. 837–840. Cerca con Google

[18] M. Lalonde, M. Beaulieu, L. Gagnon, Fast and robust optic disc detection using pyramidal decomposition and Hausdorff-based template matching, IEEE Trans. Med. Imaging 20 (11) (2001) 1193– 1200. Cerca con Google

[19] A. Osareh, M. Mirmehd, B. Thomas, R. Markham, Comparison of colour spaces for optic disc localisation in retinal images, in: Proceedings of the 16th International Conference on Pattern Recognition, vol. 1, August 2002, pp. 743–746. Cerca con Google

[20] J. Lowell, A. Hunter, D. Steel, A. Basu, R. Ryder, E. Fletcher, L. Kennedy, Optic nerve head segmentation, IEEE Trans. Med. Imaging 23 (2) (2004) 256–264. Cerca con Google

[21] E.Grisan, A.Pesce, A.Giani, M.Foracchia, A.Ruggeri,” A New tracking system for the robust extraction of retinal vessel structure”, Proceedings of the 26th Annual International Conference of the IEEE EMBS San Francisco, CA, USA • September 1-5, 2004 Cerca con Google

[22] M.Kass,A.Witkin,D.Terzopoulos “Active contour models”. International Journal of Computer Vision, pages 321-331,1988. Cerca con Google

[23] A.Amini, S.Tehrani, and E.Weimouth, Using dynamic programming for minimizing the energy of active contours in the presence of hard constraints, in Proceedings, second International Conference on Computer Vision,1988,pp. 95-99. Cerca con Google

[24] D.Williams, M. Shah, “ A fast algorithm for active contours and curvature estimation”. CVGIP:IMAGE UNDERSTANDIBG Vol.55, No.1, January, pp.14-26,1992 Cerca con Google

[25] J.Xu, O. Chutatape, E. Sung, C.Zheng, P. Chew,”Optic disk feature extraction via modified deformable model technique for glaucoma analysis” Pattern recognition 40(2007) 2063-2076 Cerca con Google

[26] M.Foracchia, E.Grisan, A.Ruggeri.”Luminosity and contrast normalization in retinal images”. Medical Image Analysis, Volume 9, issue 3, pages 179-190. Cerca con Google

[27] M.Ibanez, A.Simo. “Bayesian detection of the fovea in eye fundus angiographies”. Pattern Recogn.Lett.20,229-240. Cerca con Google

[28] Sinthanayothin,C.,Boyce, J.F., Cook,H.L.,Williamso n,T.H., 1999.Automated localisation of the optic disc,fovea, and retinal blood vessels from digital colour fundus images. Br. J. Ophthalmol. 83,902–910. Cerca con Google

[29] Goldbaum,M.,Moezzi, S.,Taylor, S.,Chatterjee ,S., Boyd, J.,Hunter,E., Jain, R., 1996. Automated diagnosis and image understanding with object extraction,object classification, and inferencing in retinal images. In: Proceedings of the IEEE International Conference on Image Processing,vol. 3. Los Alamitos,USA,pp. 695–698. Cerca con Google

[30] H.Li, O. Chutatape.” Automated feature extraction in color retinal images by a model based approach. IEEE Trans. Biomed. Eng. 51,246–254. Cerca con Google

[31] Meyer F., beucher S., “Skeletons and perceptual graphs”, Signal Process., Vol. 16, n.4,pp. 335-363, April 1989. Cerca con Google

[32] Soille P. and Vincent L., “Determing watersheds in digital pictures via flooding simulations”, Proceeding SPIE, Vol. 1360, Visual Comm. and Image Proc. ’90, Oct 1990. Cerca con Google

[33] Vincent, Luc, and Pierre Soille, "Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations," IEEE Transactions of Pattern Analysis and Machine Intelligence, Vol. 13, No. 6, June 1991, pp. 583-598. Cerca con Google

[34] T. Y. Wong, R. Klein, B. E. K. Klein, and J. M. Tielsch et al., “Retinal microvascular abnormalities, and their relation to hypertension, cardiovascular diseases and mortality,” Survey Ophthalmol., vol. 46, pp. 59–80, 2001. Cerca con Google

[35] L. D. Hubbard and R. J. Brothers et al., “Methods for evaluation of retinal microvascular abnormalities associated with hypertension sclerosis in the atherosclerosis risk in communities studies,”Ophthalmology, vol. 106, pp. 2269–80, 1999. Cerca con Google

[36] T. Y. Wong, M. Knudtson, R. Klein, B. E. K. Klein, S.M. Meuer, L. D. Hubbard, “Computer-assisted measurement of retinal vessel diameters in the Beaver Dam eye study,” Ophthalmology, vol. 111, pp. 1183–90, 2004. Cerca con Google

[37] H. Li, W. Hsu, M.L. Lee, and T.Y. Wong “Automatic grading of retinal vessel caliber,” IEEE Trans Biomed Eng, vol. 52, pp. 1352-5, 2005. Cerca con Google

[38] M.D. Knudtson, K.E. Lee, L.H. Hubbard, T.Y. Wong, R. Klein, B.E.K. Klein, “Revised formulas for summarizing retinal vessel diameters,” Current Eye Research, vol. 27, no. 3, pp. 143-149. Cerca con Google

[39] E. Grisan and A. Ruggeri, “A divide et impera strategy for automatic classification of retinal vessels into arteries and veins,” Proc. 25th Annual International Conference of IEEE-EMBS, pp. 890- 4, IEEE,New York, 2003. Cerca con Google

[40] M. De Luca,E. Grisan,A. Ruggeri.An automatic system for the estimation of generalized arteriolar narrowing in retinal images. Proc. 29th Annual International Conference of IEEE-EMBS, IEEE, Lyon, 2007 Cerca con Google

[41] Tolias Y. A. Panas S. M., “A fuzzy vessel tracking algorithm for retinal images based on fuzzy clustering,” IEEE Transactions on Medical Imaging, vol. 17, no. 2, pp. 263–273, Cerca con Google

Mar 1998. Cerca con Google

[42] Hoover A., Kouznestova V., Goldbaum M. “Locating blood vessels in retinal images by piece-wise threshold probing of a matched filter response,” IEEE Transactions on Medical Imaging,, vol. 19, no. 3, pp. 203–210, Mar 2000. Cerca con Google

[43] Lowell J., Hunter A., Steel D., Basu A., Ryder R., Kennedy R. L. “Measurement of Retinal Vesssel Widths From Fundus Images Based on 2-D Modelling,” IEEE transactions on medical imaging, vol. 23, no. 10, pp. 1196-1204, Oct 2004. Cerca con Google

[44] Leung H. et Al. “Relationships between Age, Blood Pressure, and Retinal Vessel Diameters in an Older Population” Investigative Ophthalmology & Visual Science, July Cerca con Google

2003, vol. 44, No. 7, pp. 2900-2904, Jul 2003. Cerca con Google

[45] M. De Luca,A. Giani, E. Grisan, A. Ruggeri. Detecting false vessel recognitions in retinal fundus analysis. Proc. 28th Annual International Conference of IEEE-EMBS, pp. 4449-4452, IEEE, New York, 2006 Cerca con Google

[46] C. D. Murray, The physiological principle of minimum work. i. The vascular system and the cost of blood volume., Proceedings of the National Academy of Science 12 (1926), 207–214. Cerca con Google

[47] A. V. Stanton, B. Wasan, A. Cerutti, S. Ford, R. Marsh, P. P. Sever, S. A. Thom, and A. D. Hughes, Vascular network changes in the retina with age and hypertension, Journal of Hypertension 13 (1995), 1724–1728. Cerca con Google

[48] Early Treatement Diabetic Retinopathy Study Research Group, Grading diabetic retinopathy from stereoscopic fundus photographs - am extension of the modified airlie house classification., Ophthalmology 98 (1991), 786–806. Cerca con Google

[49] N. M Keith, H. P. Wegener, and N. W. Barker, Some different types of essential hypertension: their course and prognosis, American Journal of Medicine Science 197 (1939), 336–354. Cerca con Google

[50] H. G. Scheie, Evaluation of ophthalmoscopic changes of hypertension and arterial sclerosis, Archives of Ophthalmology 49 (1953), no. 2, 117–138. Cerca con Google

[51] S. Chatterjee, S. Chattopahya, M. Hope-Ross, and P. L. Lip, Hypertensionand the eye: changing perspectives, Journal of Human Hypertension 16 (2002), 667–675. Cerca con Google

[52] The Diabetic Retinopathy Study Research Group, A modification of the airlie house classification of diabetic retinopathy, Investigative Ophthalmology and Visual Science 21 (1981), 210–226. Cerca con Google

[53] Early Treatment Diabetic Retinopathy Study Research Group, Early treatment diabetic retinopathy study design and baseline patient characteristics, Ophthalmology 98 (1991), 741–756. Cerca con Google

[54] C. P. Wilkinosn, F. L. Ferries, R. E. Klein, P. P. Lee, C. D. Agardh, M. Davies, D. Dills, A. Kampik, R. Pararajasegaram, and J. T. Vardaguer representing the global Diabetic Retinopathy Project Group, Proposed international clinical diabetic retinopathy and diabetic macular edema disease severity scale, Ophthalmolgy 110 (2003), 1677–1612. Cerca con Google

[55] S. J. Aldington, E. M. Kohner, S. Meuer, R. Klein, A. K. Sjølie, and Complication Study Group EURODIAB IDDM, Methodology for retinal photography of diabetic retinopathy: the EURODIAB IDDM Study Group, Diabetologia 38 (1995), no. 4, 437–444. Cerca con Google

[56] S. Bursell, J. D. Cavallerano, A. A. Cavallerano, A. C. Clermont, D. Birkmire-Peters, L. P. Aiello, L. M. Aiello, and the Joslin Vision Network Research Team, Stereo nonmydriatic digital-video color retinal imaging compared with early treatement diabetic retinopathy study seven standard field 35-mm stereo color for determining level of diabetic retinopathy, Ophthalmology 108 (2001), no. 3, 572–585. Cerca con Google

[57] D. Y. Lin, M. S. Blumenkranz, R. J. Brothers, D. M. Grosvenor, and for the digital diabetic screening group, The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation dor diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography, American Journal of Ophthalmology (2002), 204–213. Cerca con Google

[58] P. Massin, A. Erginay, A. Ben Mehdi, E. Vicaut, G. Quentel, Z. Victor, M. Marret, P. J. Guillausseau, and A. Gaudric, Evaluation of a new non-mydriatic digital camera for detection of diabetic retinopathy, Diabetic Medicine 20 (2003), 635–641. Cerca con Google

[59] J. A. Pugh, J. M. Jacobson, W. A. J. Van Heuven, J. A. Watters, M. R. Tuley, D. R. Lairson, R. J. Lorimor, A. S. Kapadia, and R. Velez, Screening for diabetic retinopathy. the wide angle retinal camera, Diabetes Care 16 (1993), no. 6, 889–895. Cerca con Google

[60] H. M. Herbert, K. Jordan, and D. W. Flanagan, Is screening with digital imaging using one retinal view adquate?, Eye 17 (2003), no. 3, 497–500. Cerca con Google

[61] ARIC, ARIC protocol 14A retinal photography, ARIC Coordinating Center, Department of Biostatistics (CSCC), University of North Carolina, August 1995. Cerca con Google

[62] ARIC protocol 14B retinal reading protocol, ARIC Coordinating Center, Department of Biostatistics (CSCC), University of North Carolina, May 1996. Cerca con Google

[63] G. A. Williams, I. U. Scott, J. A. Haller, A. M. Maguire, D. Marcus, and H.R. McDonald, Single-field fundus photography for diabetic retinopathy screening, Ophthalmology 111 (2004), no. 5, 1055–1012. Cerca con Google

[64] I. Liu and Y. Sun, Recursive tracking of vascular networks in angiograms based on the detection-deletion scheme, IEEE Transactions on Medical Imaging 12 (1993), no. 2, 334–341. Cerca con Google

Download statistics

Solo per lo Staff dell Archivio: Modifica questo record