Singh, D.Kaur, A.2024-01-212024-08-142024-01-212024-08-142022-04-2997816076853951938673710.1149/10701.18761ecsthttp://10.2.3.109/handle/32116/3904In 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 Societyen-USBackpropagationMagnetic resonance imagingBack-propagation neural networksEnergy-entropyEstimation methodsMRI ImageNetwork-basedNoise estimationNeural networksConference paperhttps://iopscience.iop.org/article/10.1149/10701.18761ecst