000			01971cam a2200313 a 4500
003			EG-GiCUC
008			180303s2017 ua 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.2017.Ma.W
100	0		_aManar Nasser Amin Mahmoud
245	1	0	_aWavelet-based fast computer-aided characterization of liver steatosis using conventional B-mode ultrasound images / _cManar Nasser Amin Mahmoud ; Supervised Ahmed M. Ehab Mahmoud , Muhammad Ali Rushdi
246	1	5	_aتقنية سريعة لتوصيف الكبد الدهنى بمساعدة الحاسب و استخدام المويجات و الصور التقليدية للموجات فوق الصوتية
260			_aCairo : _bManar Nasser Amin Mahmoud , _c2017
300			_a68 P. ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering
520			_aHepatic steatosis occurs when lipids accumulate in the liver and can eventually liver failure requiring a liver transplant. This work develop a computationally-efficient technique to classify fatty liver using B-mode us images. The technique relies on extracting features from the Wavelet domain using the approximation part of us images. Features include the first-order gray-level parameters, co-occurrence matrices, and local binary patterns. The technique was tested using mouse livers and image of human livers. This technique shall improve the implementation of manufacturer independent real time techniques for fatty liver classification
530			_aIssued also as CD
653		4	_aFatty liver disease
653		4	_aUltrasound images
653		4	_aWavelet packet transformation
700	0		_aAhmed Mohamed Ehab Mahmoud , _eSupervisor
700	0		_aMuhammad Ali Rushdi , _eSupervisor
905			_aNazla _eRevisor
905			_aSamia _eCataloger
942			_2ddc _cTH
999			_c65242 _d65242