文章：《Multiplicative intrinsic component optimization (MICO) for MRI bias ﬁeld estimation and tissue segmentation》
This paper proposes a new energy minimization method called multiplicative intrinsic component optimization (MICO) for joint bias ﬁeld estimation and segmentation of magnetic resonance (MR) images. The proposed method takes full advantage of the decomposition of MR images into two multiplicative components, namely, the true image that characterizes a physical property of the tissues and the bias ﬁeld that accounts for the intensity inhomogeneity, and their respective spatial properties. Bias ﬁeld estimation and tissue segmentation are simultaneously achieved by an energy minimization process aimed to optimize the estimates of the two multiplicative components of an MR image. The bias ﬁeld is iteratively optimized by using efﬁcient matrix computations, which are veriﬁed to be numerically stable by matrix analysis. More importantly, the energy in our formulation is convex in each of its variables, which leads to the robustness of the proposed energy minimization algorithm.