Garnier S J, Bilbro G L, Snyder W E, Gault J W
Department of Electrical and Computer Engineering, North Carolina State University, Raleigh 27695-7911.
J Digit Imaging. 1994 Nov;7(4):183-8. doi: 10.1007/BF03168537.
We introduce a novel technique for magnetic resonance image (MRI) restoration, using a physical model (spin equation). We determine a set of three basis images (proton density and nuclear relaxation times) from the MRI data using a nonlinear optimization method, and use those images to obtain restorations of the original image. MRIs depend nonlinearly on proton density, two nuclear relaxation times, T1 and T2, and two control parameters, echo time (TE) and relaxation time (TR). We model images as Markov random fields and introduce a maximum a posteriori restoration method, based on nonlinear optimization, which reduces noise while preserving resolution.
我们介绍了一种利用物理模型（自旋方程）进行磁共振成像（MRI）恢复的新技术。我们使用非线性优化方法从MRI数据中确定一组三个基图像（质子密度和核弛豫时间），并使用这些图像来获得原始图像的恢复结果。MRI非线性地依赖于质子密度、两个核弛豫时间T1和T2以及两个控制参数回波时间（TE）和弛豫时间（TR）。我们将图像建模为马尔可夫随机场，并引入一种基于非线性优化的最大后验恢复方法，该方法在保留分辨率的同时降低噪声。
