Rousseau F, Kim K, Studholme C, Koob M, Dietemann J L
LSIIT, UMR 7005, CNRS - Université de Strasbourg, Strasbourg.
Med Image Comput Comput Assist Interv. 2010;13(Pt 2):355-62. doi: 10.1007/978-3-642-15745-5_44.
Super-resolution techniques provide a route to studying fine scale anatomical detail using multiple lower resolution acquisitions. In particular, techniques that do not depend on regular sampling can be used in medical imaging situations where imaging time and resolution are limited by subject motion. We investigate in this work the use of a super-resolution technique for anisotropic fetal brain MR data reconstruction without modifying the data acquisition protocol. The approach, which consists of iterative motion correction and high resolution image estimation, is compared with a previously used scattered data interpolation-based reconstruction method. To optimize acquisition time, an evaluation of the influence of the number of input images and image noise is also performed. Evaluation on simulated MR images and real data show significant improvements in performance provided by the super-resolution approach.
超分辨率技术提供了一种利用多个较低分辨率采集来研究精细尺度解剖细节的途径。特别是，不依赖于规则采样的技术可用于成像时间和分辨率受受试者运动限制的医学成像情况。在这项工作中，我们研究了一种超分辨率技术用于各向异性胎儿脑磁共振数据重建，而无需修改数据采集协议。该方法由迭代运动校正和高分辨率图像估计组成，并与先前使用的基于散乱数据插值的重建方法进行了比较。为了优化采集时间，还对输入图像数量和图像噪声的影响进行了评估。对模拟磁共振图像和真实数据的评估表明，超分辨率方法在性能上有显著提升。
