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Characterizationof RenalInfection Using Ultrasonography and Texture Analysis

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dc.contributor.author Ibrahim, Ibtisam Abd Allah Fadull Elmula
dc.contributor.author Supervisor, - Elsafi Ahmed Abdalla Balla
dc.contributor.author Co - Supervisor, - Mohamed Elfadil Mohamed Gar Elnabi
dc.date.accessioned 2016-11-17T06:17:19Z
dc.date.available 2016-11-17T06:17:19Z
dc.date.issued 2016-08-21
dc.identifier.citation Ibrahim, Ibtisam Abd Allah Fadull Elmula . Characterizationof RenalInfection Using Ultrasonography and Texture Analysis \ Ibtisam Abd Allah Fadull Elmula Ibrahim ; Elsafi Ahmed Abdalla Balla .- Khartoum:Sudan University of Science and Technology,College of Medical Radiologic Sciences,2016.-112p:ill;28cm.- PhD en_US
dc.identifier.uri http://repository.sustech.edu/handle/123456789/14643
dc.description Thesis en_US
dc.description.abstract This study was done to determine the ultrasonography characteristics in renal infections (glomerulonephritis and pyelonephritis) versus normal. This study carried out in Khartoum hospital,Madanihospital ,Elmanagil hospital and Elkramit family health center , in those referred to urology department in the period from January 2014 to August 2016. A total of 234 patients were included in this study (106 were normal cases (22.6% male and 77.4% female) 128 patients had renal infections; 68 diagnosed with glomerulonephritis (38.2% males and 61.8% females) 60 with pyelonephritis (33.3% males and 66.7 females). Ultrasound scanning has been carried out, using a curve linear probe with a frequency of 3.5 to 5MHz. texrural features were extracted from kidney medulla and calycle system using a window of 3×3 pixel of first order statistics. The result of this study reveals that female was mostly affected by glomerulonephritis and pyelonephritis rather than male with male to female ratio of 1:1.6 and 1:2 respectively. Flank pain found in 82.4% associated with glomerulonephritis while 75% of pyelonephritis showed ill-defined corticomedullary differentiation. The overall accuracy using textural feature extracted from medulla was 98% while for those extracted from pelvic calycle system was 95.7%. In conclusion linear function was developed to classify other ultrasound images using textural features or ultrasonography characterizes with an error <4%. en_US
dc.description.sponsorship Sudan University of Science and Technology en_US
dc.language.iso en en_US
dc.publisher Sudan University of Science and Technology en_US
dc.subject Medical Radiologic en_US
dc.subject Ultrasonography en_US
dc.subject RenalInfection en_US
dc.title Characterizationof RenalInfection Using Ultrasonography and Texture Analysis en_US
dc.title.alternative توصيف التهاب الكلى بالتصوير بالموجات فوق الصوتية و التحليل النسيجي en_US
dc.type Thesis en_US


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