Estimation of signal and noise from Rician distributed data
نویسنده
چکیده
Conventional estimation methods applied to Rician distributed data, (such as magnitude magnetic resonance data) yield biased results. In our work, it is shown where the bias appears. Furthermore, a novel estimation technique, based on Maximum Likelihood estimation, is developed for optimal estimation of signal as well as noise from Rician distributed data. It is shown that the proposed method is superior in terms of mean squared error compared to the performance of conventional estimation techniques.
منابع مشابه
روشی نوین در کاهش نوفه رایسین از مقدار بزرگی سیگنال دیفیوژن در تصویربرداری تشدید مغناطیسی (MRI)
The true MR signal intensity extracted from noisy MR magnitude images is biased with the Rician noise caused by noise rectification in the magnitude calculation for low intensity pixels. This noise is more problematic when a quantitative analysis is performed based on the magnitude images with low SNR(<3.0). In such cases, the received signal for both the real and imaginary components will fluc...
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