fa کاهش نوفه در تصویربرداری تشدید مغناطیسی با استفاده از الگوریتم تخمین بیزین مقالات گروه علائم حیاتی ( مرتبط با مهندسی پزشکی) Paper پژوهشي Research <div style="text-align: justify;"><strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">تصویربرداری تشدید مغناطیسی</span></span></span></strong><a href="#_ftn1" name="_ftnref1" title=""><strong><span style="color:black;"><span style="font-size:10.0pt;"><span dir="LTR"><strong><span style="color:black;"><span style="font-family:Times New Roman Bold,serif;"><span style="font-size:8.0pt;">[1]</span></span></span></strong></span></span></span></strong></a> <strong><span dir="LTR"><span style="color:black;"><span style="font-family:Times New Roman Bold,serif;"><span style="font-size:8.0pt;">(MRI)</span></span></span></span></strong><strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;"> که اساس آن بر پایه تشدید مغناطیسی هسته</span></span></span></strong><strong><span dir="LTR"><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">&lrm;</span></span></span></span></strong><strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">ای بنا نهاده شده، به</span></span></span></strong><strong><span dir="LTR"><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">&lrm;</span></span></span></span></strong><strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">عنوان یک روش بارز در زمینه کاربردهای پزشکی مطرح است. به</span></span></span></strong><strong><span dir="LTR"><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">&lrm;</span></span></span></span></strong><strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">دلیل وضوح مناسب و فناوری کم‌ضرر،</span></span></span></strong><strong><span dir="LTR"><span style="color:black;"><span style="font-family:Times New Roman Bold,serif;"><span style="font-size:8.0pt;">MRI</span></span></span></span></strong><strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;"> در کاربردهای بالینی بسیار مورد توجه قرار گرفته است. کیفیت تصاویر</span></span></span></strong><strong><span dir="LTR"><span style="color:black;"><span style="font-family:Times New Roman Bold,serif;"><span style="font-size:8.0pt;"> MR </span></span></span></span></strong><strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">نقش کلیدی</span></span></span></strong><strong><span dir="LTR"><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">&lrm;</span></span></span></span></strong><strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;"> در نحوه تشخیص پزشک ایفا می</span></span></span></strong><strong><span dir="LTR"><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">&lrm;</span></span></span></span></strong><strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">کند؛ اما به</span></span></span></strong><strong><span dir="LTR"><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">&lrm;</span></span></span></span></strong><strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">دلیل ایجاد نوفه حین فرآیند تصویربرداری، اغلب کیفیت تصاویر دریافتی کاهش می‌یابد. از این‌رو حذف نوفه جهت ارتقای قابلیت تشخیص بسیار مورد توجه قرار گرفته است. نوفه موجود در تصاویر</span></span></span></strong><strong><span dir="LTR"><span style="color:black;"><span style="font-family:Times New Roman Bold,serif;"><span style="font-size:8.0pt;"> MR</span></span></span></span></strong><strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;"> که منجر به کاهش شدت نور تصویر شده و بایاس وابسته به سیگنال ایجاد می</span></span></span></strong><strong><span dir="LTR"><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">&lrm;</span></span></span></span></strong><strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;">کند، به بهترین شکل با تابع توزیع رایسین مدل می‌شود. به‌طور‌کلی هدف از این پژوهش پیداکردن تابع چگالی احتمال پیشین مناسبی برا یسیگنال بدون نوفه</span></span></span></strong><a href="#_ftn2" name="_ftnref2" title=""><strong><span style="color:black;"><span style="font-size:10.0pt;"><span dir="LTR"><strong><span style="color:black;"><span style="font-family:Times New Roman Bold,serif;"><span style="font-size:8.0pt;">[2]</span></span></span></strong></span></span></span></strong></a> <strong><span dir="LTR"><span style="color:black;"><span style="font-family:Times New Roman Bold,serif;"><span style="font-size:8.0pt;">MR</span></span></span></span></strong><strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;"> و استفاده از تخمین بیزین در راستای کاهش نوفه تصویر است که در مقایسه با سایر روش&shy;های گروه آماری روشی کم‌هزینه با پیچیدگی محاسباتی پایین&shy;تر است.</span></span></span></strong> <strong><span style="color:black;"><span style="font-family:B Nazanin;"><span style="font-size:10.0pt;"></span></span></span></strong></div> <div><div style="text-align: justify;"></div> <hr align="left" size="1" width="33%" ><div style="text-align: justify;"></div> <div id="ftn1" style="text-align: justify;"><a href="#_ftnref1" name="_ftn1" title=""><span style="font-family:Times New Roman,serif;"><span style="font-size:9.0pt;"><span style="font-family:Times New Roman,serif;"><span style="font-size:9.0pt;">[1]</span></span></span></span></a><span style="font-size:9.0pt;"> Magnetic Resonance Imaging</span><span style="font-size:9.0pt;"></span></div> <div style="text-align: justify;"></div> <div id="ftn2" style="text-align: justify;"><a href="#_ftnref2" name="_ftn2" title=""><span style="font-family:Times New Roman,serif;"><span style="font-size:9.0pt;"><span style="font-family:Times New Roman,serif;"><span style="font-size:9.0pt;">[2]</span></span></span></span></a><span style="font-size:9.0pt;"> Noiseless signal</span></div> </div> <div style="text-align: justify;"><strong>Magnetic Resonance Imaging (MRI) is a notable medical imaging technique that is based on Nuclear Magnetic Resonance (NMR). MRI is a safe imaging method with high contrast between soft tissues, which made it the most popular imaging technique in clinical applications. MR Image&#39;s visual quality plays a vital role in medical diagnostics that can be severely corrupted by existing noise during the acquisition process. Therefore, the denoising of these images has great importance in medical applications. During the last decades, lots of MR denoising approaches from various groups of techniques have been proposed that can be classified into two general groups of acquisition-based noise reduction and post-acquisition denoising methods. The first group&#39;s approaches will add imaging time and led to a much time-consuming process. The second group&#39;s issues are its complicated mathematical equations required for image denoising, in which stochastic algorithms are usually required to solve these complex equations.</strong><br> <strong>This study aims to find an appropriate statical post-acquisition denoising MR imaging method based on the Bayesian technique. Finding the appropriate prior density function also has great importance since the Bayesian technique&#39;s performance is related to its prior density function. In this study, the uniform distribution has been applied as the prior density function. The prior uniform distribution function will reduce the Bayesian algorithm to its simplest possible state and lower computational complexity and time consumption. The proposed method can solve the numerical problems with an adequate timing process without complex algorithms and remove noise in less than 120 seconds on average in all cases. To quantitatively assess image improvement, we used the Structural Similarity Function (SSIM) in MATLAB. The similarity with this function shows an average improvement of more than 0.1 in all images. Considering the results, it can be concluded that combining the uniform distribution function as a prior density function and the Bayesian algorithm can significantly reduce the image&#39;s noise without the time and computational cost.</strong></div> تخمین بیزین, توزیع رایس, تصویربرداری تشدید مغناطیسی Bayesian estimation, Rician distribution, Magnetic Resonance Imaging 101 108 http://jsdp.rcisp.ac.ir/browse.php?a_code=A-10-951-3&slc_lang=fa&sid=1 Javad Kazemitabar سید جواد کاظمی تبار j.kazemitabar@nit.ac.ir 10031947532846009357 10031947532846009357 Yes Babol Noshirvani University of Technology دانشگاه صنعتی نوشیروانی بابل Mitra Tavakkoli میترا توکلی kazemita@hotmail.com 10031947532846009358 10031947532846009358 No Babol Noshirvani University of Technology دانشگاه صنعتی نوشیروانی بابل