Please use this identifier to cite or link to this item: https://repository.sustech.edu/handle/123456789/13917
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dc.contributor.authorahmed, Ashraf Abrahim Abdallah
dc.contributor.authorSupervisor,- Mawia Ahmed Hassan
dc.date.accessioned2016-08-17T05:10:38Z
dc.date.available2016-08-17T05:10:38Z
dc.date.issued2016-01-10
dc.identifier.citationahmed, Ashraf Abrahim Abdallah . MRI Phase Mismapping Image Artifact correction / Ashraf Abrahim Abdallah ahmed ; Mawia Ahmed Hassan .- khartoum: Sudan University of Science and Technology , College of Engineering , 2016 .- 79p. :ill. ;28cm .-M.Sc.en_US
dc.identifier.urihttp://repository.sustech.edu/handle/123456789/13917
dc.descriptionThesisen_US
dc.description.abstractMRI machine one of the most significant diagnostic modalities. The only restriction that affects the MRI image is that imaging procedure take very long time comparing with CT scan and other diagnostic modalities, thus old patient, children and the illness people cannot stay without movement inside the magnet therefore artifact will affect the MRI image and several miss analysis may occur especially in the neuroanatomical measurements. Many procedure has been use to solve this problem for example before during and after the MRI image reconstruction. in this study the effectiveness of a new retrospective motion correction technique has been applied and tested. Three different section MRI image ( coronal, sagittal and axial ) were used and given different correction results. That was by develop algorithm to correct the motion blur in the MRI image that corrupted by patient rigid motion. Wiener filter was used as the main restoration procedure by means of angle and length estimation of the motion blur. Motion blur angle and length were estimated using Hough transformer. The technique was applied and tested several time, it gave acceptable correction result in the sagittal image compare with the coronal one but the technique was result in the least motion blur correction in the axial image. Signal to noise ratio was calculated for every image to figure out the degree of the correction technique according to the different estimated angle and length. Signal to noise ratio values were to be through with correction result.en_US
dc.description.sponsorshipSudan University of Science and Technologyen_US
dc.language.isoenen_US
dc.publisherSudan University of Science and Technologyen_US
dc.subjectBiomedical Engineeringen_US
dc.subjectImage Artifact correctionen_US
dc.subjectMRI Phase Mismappingen_US
dc.titleMRI Phase Mismapping Image Artifact correctionen_US
dc.title.alternativeتصحيح التشوهات الناتجه عن فقدان الطور في صور الرنين المغنطيسيen_US
dc.typeThesisen_US
Appears in Collections:Masters Dissertations : Engineering

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