Cui Chen, Wu Xiaodong, Newell John D, Jacob Mathews
Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, Iowa, USA.
Magn Reson Med. 2015 Mar;73(3):1289-99. doi: 10.1002/mrm.25193. Epub 2014 Mar 6.
This article focuses on developing a novel noniterative fat water decomposition algorithm more robust to fat water swaps and related ambiguities.
Field map estimation is reformulated as a constrained surface estimation problem to exploit the spatial smoothness of the field, thus minimizing the ambiguities in the recovery. Specifically, the differences in the field map-induced frequency shift between adjacent voxels are constrained to be in a finite range. The discretization of the above problem yields a graph optimization scheme, where each node of the graph is only connected with few other nodes. Thanks to the low graph connectivity, the problem is solved efficiently using a noniterative graph cut algorithm. The global minimum of the constrained optimization problem is guaranteed. The performance of the algorithm is compared with that of state-of-the-art schemes. Quantitative comparisons are also made against reference data.
The proposed algorithm is observed to yield more robust fat water estimates with fewer fat water swaps and better quantitative results than other state-of-the-art algorithms in a range of challenging applications.
The proposed algorithm is capable of considerably reducing the swaps in challenging fat water decomposition problems. The experiments demonstrate the benefit of using explicit smoothness constraints in field map estimation and solving the problem using a globally convergent graph-cut optimization algorithm.
本文着重于开发一种新型的非迭代脂肪水分解算法，该算法对脂肪水交换及相关模糊性具有更强的鲁棒性。
将场图估计重新表述为一个约束曲面估计问题，以利用场的空间平滑性，从而最小化恢复过程中的模糊性。具体而言，相邻体素之间场图诱导的频率偏移差异被约束在一个有限范围内。上述问题的离散化产生了一种图优化方案，其中图的每个节点仅与少数其他节点相连。由于图的低连通性，使用非迭代图割算法可高效解决该问题。保证了约束优化问题的全局最小值。将该算法的性能与现有最先进方案的性能进行比较。还与参考数据进行了定量比较。
在一系列具有挑战性的应用中，观察到所提出的算法比其他现有最先进算法产生更稳健的脂肪水估计，脂肪水交换更少且定量结果更好。
所提出的算法能够在具有挑战性的脂肪水分解问题中显著减少交换。实验证明了在现场图估计中使用显式平滑约束并使用全局收敛的图割优化算法解决问题的益处。
