Noise Estimation Using Back Propagation Neural Networks
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Date
2022-04-29T00:00:00
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Publisher
Institute of Physics
Abstract
In this paper, a new Backpropagation Neural Network-based noise estimation method is proposed to estimate Rician noise from MRI images. To train BNN features of MRI images such as, contrast, homogeneity, dissimilarity, asm, energy, entropy, meanx, meany, meanglcm, varx, vary, varglcm, correlation, skewx, skewy, skew, kurtosisx, kurtosisy, kurtosis etc are used. For training BNN, four hundred fifty images are used which are downloaded from Brain web. � The Electrochemical Society
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Keywords
Backpropagation, Magnetic resonance imaging, Back-propagation neural networks, Energy-entropy, Estimation methods, MRI Image, Network-based, Noise estimation, Neural networks