دراسة نظرية وتحليلية لتأثير الضجيج في التصوير بالرنين المغناطيسي نحو أنظمة تصوير أفضل

الموضوعات

علوم تطبيقية وتكنولوجية

روابط وملفات

التعريف والنوع

رقم الوثيقة

04892c37-d9c2-40f9-bf7d-77c876521b9e

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل ماجيستير

نوع الملف

pdf text

أسماء الملفات

1966390_1.pdf

بيانات النشر

ألقاب المؤلفين

[{"name_ar":"حسان حلواني","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"فواز بدور","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"ميساء سنان","title_ar":"اعداد","title_en":"Preparation"}]

اللغة

Arabic

المصدر والدورية

اسم المصدر

دراسة نظرية وتحليلية لتأثير الضجيج في التصوير بالرنين المغناطيسي نحو أنظمة تصوير أفضل

المحتوى والصفحات

عدد الصفحات

99

ترجمة الملخص

Research includes presentation of the physical and mathematical foundations and principle of the work in a magnetic resonance imaging (MRI) and mechanism constitute the signal. It was mentioned to the different types of noise associated with the signal in the magnetic resonance images for example the thermal noise and the sample losses contribution of imaging parameters, in noise variance, and to address the mechanism of the formation of the noise. Group of Algorithms were created in an environment of Matlab to study and analyze: rice probability density function for different values of the ration of SNR, generalized Rice distribute for different values for K, which represents the number of orthogonal Cartesian directions, the standard deviation of the noise of the conventional and maximum likelihood ML estimators as function of the number of points N, the number of orthogonal Cartesian directions K, and the performance of the conventional and probability maximum likelihood ML estimators. It was found that the Gauss distribution in probability density function gives a better signal and less noise for larger magnetization values, and it's happening the improvement in the image in generalized Rice distribution for large values K at SNR=3. As it seemed that the standard deviation of the noise increases with increasing the number of points N, and by decreasing the number of orthogonal Cartesian directions K, and the standard deviation of the noise will be less than one order for estimator ML compared with the conventional estimator, meaning that the image will be better by using the estimator ML.In this research excitation and relaxation in a magnetic resonance , and mechanism of constitute the signal have studied. Also has discussed the conventional and the Maximum likelihood methods to estimate of the signal. The estimation of the longitudinal and transverse relaxation parameters T1, T2play a major role in the stability of image contrast, has proposed ML technique in estimating T1, T2by knowing Rice distributed. M experimental values were determined to estimate the optimal signal. been studied Log (L) as a function of A, that's been drawn. Group of algorithms was created: -to determine the values of M by knowing values of A, SNR the experimental using numerical methods (Newton -Rafson) and expanding in a series of Tyler. -To estimate the longitudinal and transverse relaxation times T1, T2using two methods ML and LS as a function of SNR. been searching for the best signal which is possible when approaching the value of magnetization beam M of the value of the A, using numerical methods (Newton -Rafson), and expanding in a series of Tyler, deviation observed in the Method of ML in estimating when the values of SNR low, but remains less than the deviation observed in the method LS. As it seemed when estimating T2the presence of a clear difference between the two methods ML and LS at low SNR values.

إشراف وإعداد

الإشراف

حسان حلواني, فواز بدور

الإعداد

ميساء سنان

الاقتباسات الببليوغرافية