Please use this identifier to cite or link to this item: https://repository.sustech.edu/handle/123456789/14643
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dc.contributor.authorIbrahim, Ibtisam Abd Allah Fadull Elmula-
dc.contributor.authorSupervisor, - Elsafi Ahmed Abdalla Balla-
dc.contributor.authorCo - Supervisor, - Mohamed Elfadil Mohamed Gar Elnabi-
dc.date.accessioned2016-11-17T06:17:19Z-
dc.date.available2016-11-17T06:17:19Z-
dc.date.issued2016-08-21-
dc.identifier.citationIbrahim, 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.- PhDen_US
dc.identifier.urihttp://repository.sustech.edu/handle/123456789/14643-
dc.descriptionThesisen_US
dc.description.abstractThis 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.sponsorshipSudan University of Science and Technologyen_US
dc.language.isoenen_US
dc.publisherSudan University of Science and Technologyen_US
dc.subjectMedical Radiologicen_US
dc.subjectUltrasonographyen_US
dc.subjectRenalInfectionen_US
dc.titleCharacterizationof RenalInfection Using Ultrasonography and Texture Analysisen_US
dc.title.alternativeتوصيف التهاب الكلى بالتصوير بالموجات فوق الصوتية و التحليل النسيجيen_US
dc.typeThesisen_US
Appears in Collections:PhD theses :Medical Radiologic Science

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