000			02291cam a2200337 a 4500
003			EG-GiCUC
005			20250223031403.0
008			160106s2015 ua h f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.13.03.M.Sc.2015.Ah.A
100	0		_aAhmed Sayed Elhossiny Adawy
245	1	0	_aAutomatic detection of retinal fundus images features for detection of diabetic retinopathy / _cAhmed Sayed Elhossiny Adawy ; Supervised Amr Abdelrahman Shaarawi , Amr Abdelrahim Mustafa Eldeeb
246	1	5	_aالكشف التلقائى لميزات صور الشبكية لقاع العين للكشف عن اعتلال الشبكية السكرى
260			_aCairo : _bAhmed Sayed Elhossiny Adawy , _c2015
300			_a80 P. : _bfacsimiles ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering
520			_aThe main purpose of this research is to build a system capable of identifying the normal anatomical structure of the retina and the bright lesions which are caused by diabetic retinopathy. This is done by digital image processing technologies. In the first step Gabor filters were employed to increase the intensity contrast between the blood vessel and the background. Next we used entropic threshold, in order to classify each pixel in the blood vessels and other areas. Then to determine the optical disk location, we used iterative thresholding. Then we applied the geometric model that relied on the implicit active contour in order to accurately determine the boundary of the optical disk. In the final stage entropic threshold was applied to determine bright lesions such as hard exudates and cotton patches in the fundus images. This method achieved a sensitivity and specificity of 95.8% and 90.5%, respectively
530			_aIssued also as CD
653		4	_aDiabetic Retinopathy
653		4	_aFundus Retinal Digital Image
653		4	_aGabor Filter
700	0		_aAmr Abdelrahim Mustafa Eldeeb , _eSupervisor
700	0		_aAmr Abdelrahman Shaarawi , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aNazla _eRevisor
905			_aSoheir _eCataloger
942			_2ddc _cTH
999			_c54281 _d54281