Noise Estimation Using Back Propagation Neural Networks
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
Journal
ECS Transactions
Access Type
Closed Access