Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
J Magn Reson Imaging. 2011 Jun;33(6):1464-73. doi: 10.1002/jmri.22525.
To quickly and robustly separate fat/water components of 7T MR images in the presence of field inhomogeneity for the study of metabolic disorders in small animals.
Starting with a Markov random field (MRF) based formulation for the 3-point Dixon separation problem, we incorporated new implementation strategies, including stability tracking, multiresolution image pyramid, and improved initial value generation. We term the new method FLAWLESS (Fast Lipid And Water Levels by Extraction with Spatial Smoothing).
Compared with non-MRF techniques, FLAWLESS decreased the fat-water swapping mistakes in all of the three-dimensional (3D) animal volumes that we tested. FLAWLESS converged in approximately 1/60th of the computation time of other MRF approaches. The initial value generation of FLAWLESS further improved robustness to field inhomogeneity in 3D volume data.
We have developed a novel 3-point Dixon technique found to be useful for high field small animal imaging. It is being used to assess lipid depots and metabolic disorders as a function of genes, diet, age, and therapy.
在存在磁场不均匀的情况下，快速稳健地分离 7T MR 图像的脂肪/水成分，用于研究小动物的代谢紊乱。
从基于马尔可夫随机场（MRF）的 3 点 Dixon 分离问题的公式出发，我们采用了新的实现策略，包括稳定性跟踪、多分辨率图像金字塔和改进的初始值生成。我们将新方法命名为 FLAWLESS（通过空间平滑提取快速脂质和水水平）。
与非 MRF 技术相比，FLAWLESS 减少了我们测试的所有三个维度（3D）动物体积中的脂肪-水交换错误。FLAWLESS 的收敛时间约为其他 MRF 方法的 1/60。FLAWLESS 的初始值生成进一步提高了对 3D 体数据中磁场不均匀性的鲁棒性。
我们开发了一种新的 3 点 Dixon 技术，该技术已被证明对高磁场小动物成像有用。它正被用于评估脂质储存和代谢紊乱作为基因、饮食、年龄和治疗的函数。
