In early-stage diabetic retinopathy, risk of cardiac events after implantation of sirolimus-eluting stent is higher than after coronary artery bypass surgery

Masuzawa, Akihiro; Ohno, Takayuki; Takamoto, Shinichi; Motomura, Noboru; Ōno, Minoru; Fujita, Hideo; Ando, Jiro; Morita, Toshihiro; Hirata, Yasunobu; Nagai, Ryozo; Hirose, Akira; Shigeeda, Takashi; Kato, Satoshi; Araie, Makoto

doi:10.1016/j.jjcc.2008.09.003

Cited by 2 publications

(1 citation statement)

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“…For this reason, early detection as well as the periodic screening of DR potentially helps in reducing the progression of this disease and in preventing the subsequent loss of vision capability 2 . Patient with DR have an increased risk of death from coronary disease and myocardial infarction 3 . The people who are affected by DR have excess risks of systemic vascular complications, including sub clinical and clinical stroke, coronary heart disease and nephropathy 5 .…”

Section: Introductionmentioning

confidence: 99%

Effective Segmentation of Optic Disc in Retinal images for diagnosing Eye Diseases that leads to Blindness

Karkuzhali¹,

Manimegalai²,

Santhi³

2015

Biomed. Pharmacol. J.

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Human Eye is one of the most sophisticated organ, with cornea ,retinal pigment epithelium, bruch membrane, macula, vitreous body, retina and optic nerve. Retinal image analysis is broadly used for screening the patients affected from sight threatening eye diseases like Diabetic Retinopathy (DR) and glaucoma. Optic disc (OD) margin is the mandatory landmark in establishing a frame of reference of classifying retinal and optic nerve pathology. Trustworthy and efficient OD localization and segmentation are important tasks in automatic eye disease screening. This paper presents a fully automated method for OD segmentation algorithm developed for retinal disease screening. First, preprocessing step used to remove noise by illumination correction and contrast enhancement. Second, a thresholding technique using Atanassov's intuitionistic fuzzy set (A-IFS) is employed. This approach uses A-IFS histon, an encrustation of the histogram consist of the pixels that belong to the set of similar pixels, in roughness index A-IFS histon & histogram correlated to upper and lower approximations and optimum threshold value is identified which pixel belong to background or to object(OD). This approach is evaluated by means of three publicly available databases DRIVE, MESSIDOR, DIARETDB0, the experimental outcome shows that the overall performance is with 99% correct optic disc localization.

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Section: Introductionmentioning

confidence: 99%