ALTAIR: Supervised Methodology to Obtain Retinal Vessels Caliber



A back of the eye examination allows performing a noninvasive evaluation of the retinal microcirculation, as well as of the vascular damage induced by multiple cardiovascular risk factors. The objective of this work is to study the existing needs to lead to the development and validation (reliability and validity) of a methodology able to extract all the information from the images of the back of the eye to solve the studied needs. Its development will subsequently allow analyzing its utility in various clinical environments. Currently there are different works that evaluate the thickness of the retinal veins and arteries, but they require either full intervention by an observer or no intervention at all, so when facing incorrect analysis (none of them achieves a 100 % accuracy in automatic analysis) erroneous results can be a serious problem when drawing conclusions. The proposed solution refers to the second group (automatic), but providing a supervisor the possibility to interfere with the analysis when any kind of error is produced, which ideally will not happen many times. Thanks to this the possible subjectivity that can be introduced by the supervisor does not affect the final result of the analysis.


Image analysis; Fundus images; Vessels caliber

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Chamoso, P., García-Ortiz, L., Recio-Rodríguez, J. I., & Gómez-Marcos, M. A. (2014, January). Platform Image Processing Applied to the Study of Retinal Vessels. In 8th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2014) (pp. 21-30). Springer International Publishing.

Chapman, N., Witt, N., Gao, X., Bharath, A. A., Stanton, A. V., Thom, S. A., & Hughes, A. D. (2001). Computer algorithms for the automated measurement of retinal arteriolar diameters. British Journal of Ophthalmology, 85(1), 74-79.

Dahlöf, B., Stenkula, S., & Hansson, L. (1992). Hypertensive retinal vascular changes: relationship to left ventricular hypertrophy and arteriolar changes before and after treatment. Blood pressure, 1(1), 35-44.

Díaz, F., FdezLRiverola, F., & Corchado, J. M. (2006). geneLCBR: A CASELBASED REASONIG TOOL FOR CANCER DIAGNOSIS USING MICROARRAY DATA SETS. Computational Intelligence, 22(3L4), 254-268.

Ege, B. M., Hejlesen, O. K., Larsen, O. V., Møller, K., Jennings, B., Kerr, D., & Cavan, D. A. (2000). Screening for diabetic retinopathy using computer based image analysis and statistical classification. Computer methods and programs in biomedicine, 62(3), 165-175.

García-Ortiz, L., Parra-Sanchez, J., Recio-Rodríguez, J. I., Agudo-Conde, C., González-Elena, L. J., & Gómez-Marcos, M. A. (2013). El papel de las venas de la retina en el riesgo cardiovascular. Hipertensión y Riesgo Vascular, 30(3), 92-100.

García-Ortiz, L., Recio-Rodríguez, J. I., Parra-Sanchez, J., Elena, L. J. G., Patino-Alonso, M. C., Agudo-Conde, C., ... & Gómez-Marcos, M. A. (2012). A new tool to assess retinal vessel caliber. Reliability and validity of measures and their relationship with cardiovascular risk. Journal of hypertension, 30(4), 770-777.

Klette, R. (2014). Concise Computer Vision.

Leibowitz, H. M., Krueger, D. E., Maunder, L. R., Milton, R. C., Kini, M. M., Kahn, H. A., ... & Dawber, T. R. (1979). The Framingham Eye Study monograph: an ophthalmological and epidemiological study of cataract, glaucoma, diabetic retinopathy, macular degeneration, and visual acuity in a general population of 2631 adults, 1973-1975. Survey of ophthalmology, 24(Suppl), 335-610.

Martinez-Perez, M. E., Hughes, A. D., Thom, S. A., Bharath, A. A., & Parker, K. H. (2007). Segmentation of blood vessels from red-free and fluorescein retinal images. Medical image analysis, 11(1), 47-61.

Matsopoulos, G. K., Mouravliansky, N. A., Delibasis, K. K., & Nikita, K. S. (1999). Automatic retinal image registration scheme using global optimization techniques. Information Technology in Biomedicine, IEEE Transactions on, 3(1), 47-60.

McGeechan, K., Liew, G., Macaskill, P., Irwig, L., Klein, R., Klein, B. E., ... & Wong, T. Y. (2009). Meta-analysis: retinal vessel caliber and risk for coronary heart disease. Annals of internal medicine, 151(6), 404-413.

McGeechan, K., Liew, G., Macaskill, P., Irwig, L., Klein, R., Sharrett, A. R., ... & Wong, T. Y. (2008). Risk prediction of coronary heart disease based on retinal vascular caliber (from the Atherosclerosis Risk In Communities [ARIC] Study). The American journal of cardiology, 102(1), 58-63.

Patton, N., Aslam, T. M., MacGillivray, T., Deary, I. J., Dhillon, B., Eikelboom, R. H., ... & Constable, I. J. (2006). Retinal image analysis: concepts, applications and potential. Progress in retinal and eye research, 25(1), 99-127.

Sanchez, C. I., Hornero, R., López, M. I., Aboy, M., Poza, J., & Abasolo, D. (2008). A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis. Medical Engineering & Physics, 30(3), 350-357.

Sekhar, S., Al-Nuaimy, W., & Nandi, A. K. (2008, May). Automated localisation of retinal optic disk using Hough transform. In Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on (pp. 1577-1580). IEEE.

Tanabe, Y., Kawasaki, R., Wang, J. J., Wong, T. Y., Mitchell, P., Daimon, M., ... & Yamashita, H. (2010). Retinal arteriolar narrowing predicts 5Lyear risk of hypertension in Japanese people: the Funagata Study. Microcirculation, 17(2), 94-102.

Tikellis, G., Arnett, D. K., Skelton, T. N., Taylor, H. W., Klein, R., Couper, D. J., ... & Wong, T. Y. (2008). Retinal arteriolar narrowing and left ventricular hypertrophy in African Americans. The Atherosclerosis Risk in Communities (ARIC) study. American journal of hypertension, 21(3), 352-359.

Winder, R. J., Morrow, P. J., McRitchie, I. N., Bailie, J. R., & Hart, P. M. (2009). Algorithms for digital image processing in diabetic retinopathy. Computerized Medical Imaging and Graphics, 33(8), 608-622.

Wong, T. Y., Duncan, B. B., Golden, S. H., Klein, R., Couper, D. J., Klein, B. E., ... & Schmidt, M. I. (2004). Associations between the metabolic syndrome and retinal microvascular signs: the Atherosclerosis Risk In Communities study. Investigative ophthalmology & visual science, 45(9), 2949-2954.

Wong, T. Y., Islam, F. A., Klein, R., Klein, B. E., Cotch, M. F., Castro, C., ... & Shahar, E. (2006). Retinal vascular caliber, cardiovascular risk factors, and inflammation: the multi-ethnic study of atherosclerosis (MESA). Investigative ophthalmology & visual science, 47(6), 2341-2350.

Wong, T. Y., Klein, R., Sharrett, A. R., Duncan, B. B., Couper, D. J., Tielsch, J. M., ... & Hubbard, L. D. (2002). Retinal arteriolar narrowing and risk of coronary heart disease in men and women: the Atherosclerosis Risk in Communities Study. Jama, 287(9), 1153-1159

Wong, T. Y., Klein, R., Couper, D. J., Cooper, L. S., Shahar, E., Hubbard, L. D., ... & Sharrett, A. R. (2001). Retinal microvascular abnormalities and incident stroke: the Atherosclerosis Risk in Communities Study. The Lancet, 358(9288), 1134-1140.

Yatsuya, H., Folsom, A. R., Wong, T. Y., Klein, R., Klein, B. E., & Sharrett, A. R. (2010). Retinal microvascular abnormalities and risk of lacunar stroke atherosclerosis risk in communities study. Stroke, 41(7), 1349-1355.

Zana, F., & Klein, J. C. (1997, July). Robust segmentation of vessels from retinal angiography. In Digital Signal Processing Proceedings, 1997. DSP 97., 1997 13th International Conference on (Vol. 2, pp. 1087-1090). IEEE.

Zana, F., & Klein, J. C. (1999). A multimodal registration algorithm of eye fundus images using vessels detection and Hough transform. Medical Imaging, IEEE Transactions on, 18(5), 419-428.


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