This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixin

计算SENSE重建图像中的g-factor,这是并行磁共振成像SENSE算法的关键一步-G-factor is the metric to quantify the amplificaiton of noise power in reconstructing SENSE accelerated image. The detail was presented in Pruessmann s 1999 Magn. Reson. Med. paper. In theory, g-factor is t