Witoszynskyj Stephan, Rauscher Alexander, Reichenbach Jürgen R, Barth Markus
Medical Physics Group, Institute for Diagnostic and Interventional Radiology, Friedrich Schiller University, Jena, Germany.
Med Image Anal. 2009 Apr;13(2):257-68. doi: 10.1016/j.media.2008.10.004. Epub 2008 Oct 18.
We present a fully automated phase unwrapping algorithm (Phi UN) which is optimized for high-resolution magnetic resonance imaging data. The algorithm is a region growing method and uses separate quality maps for seed finding and unwrapping which are retrieved from the full complex information of the data. We compared our algorithm with an established method in various phantom and in vivo data and found a very good agreement between the results of both techniques. Phi UN, however, was significantly faster at low signal to noise ratio (SNR) and data with a more complex phase topography, making it particularly suitable for applications with low SNR and high spatial resolution. Phi UN is freely available to the scientific community.
我们提出了一种针对高分辨率磁共振成像数据进行优化的全自动相位解缠算法（Phi UN）。该算法是一种区域生长方法，使用从数据的完整复数信息中检索出的单独质量图来寻找种子点和解缠。我们在各种体模和体内数据中将我们的算法与一种既定方法进行了比较，发现两种技术的结果之间具有很好的一致性。然而，在低信噪比（SNR）和具有更复杂相位地形的数据情况下，Phi UN的速度明显更快，这使得它特别适用于低SNR和高空间分辨率的应用。Phi UN可供科学界免费使用。
