Woo Jonghye, Bai Ying, Roy Snehashis, Murano Emi Z, Stone Maureen, Prince Jerry L
University of Maryland, Baltimore MD 21201; Johns Hopkins University, Baltimore MD 21218.
HeartFlow Inc., Redwood City CA 94063.
Proc SPIE Int Soc Opt Eng. 2012 Feb 4;8314. doi: 10.1117/12.911445. Epub 2012 Feb 23.
Magnetic resonance (MR) images of the tongue have been used in both clinical medicine and scientific research to reveal tongue structure and motion. In order to see different features of the tongue and its relation to the vocal tract it is beneficial to acquire three orthogonal image stacks-e.g., axial, sagittal and coronal volumes. In order to maintain both low noise and high visual detail, each set of images is typically acquired with in-plane resolution that is much better than the through-plane resolution. As a result, any one data set, by itself, is not ideal for automatic volumetric analyses such as segmentation and registration or even for visualization when oblique slices are required. This paper presents a method of super-resolution reconstruction of the tongue that generates an isotropic image volume using the three orthogonal image stacks. The method uses preprocessing steps that include intensity matching and registration and a data combination approach carried out by Markov random field optimization. The performance of the proposed method was demonstrated on five clinical datasets, yielding superior results when compared with conventional reconstruction methods.
舌部的磁共振（MR）图像已被应用于临床医学和科学研究中，以揭示舌部结构和运动情况。为了观察舌部的不同特征及其与声道的关系，获取三个正交图像堆栈（例如轴向、矢状和冠状体积）是有益的。为了同时保持低噪声和高视觉细节，每组图像通常以面内分辨率进行采集，该分辨率远高于层面分辨率。因此，任何一个数据集本身对于诸如分割和配准等自动体积分析而言都不理想，甚至在需要斜切片进行可视化时也不理想。本文提出了一种舌部超分辨率重建方法，该方法利用三个正交图像堆栈生成各向同性图像体积。该方法使用包括强度匹配和配准在内的预处理步骤，以及通过马尔可夫随机场优化进行的数据组合方法。在五个临床数据集上验证了所提方法的性能，与传统重建方法相比产生了更优的结果。
