ENTROPY BASED NON-INTERACTIVE NYQUIST GHOST CORRECTION ALGORITHM

基于熵的非交互式奈奎斯特鬼影校正算法

• 批准号: 7358809
• 负责人: STEFAN SKARE
• 金额: $ 2.49万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-06-01 至 2007-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7358809
• 关键词: ENTROPY; BASED; NON; INTERACTIVE; NYQUIST

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Introduction. Nyquist ghosting occurs in EPI due to misalignment between odd and even echoes. For this reason, clinical EPI scans are commonly performed with a reference scan incorporated into the prescan process from which phase information can be used to correct ghosting errors. For multi-shot, multi-coil and multi-slice acquisitions, this additional scan can often exceed a minute, which may be crucial in cases of acute stroke, for example. An interesting alternative to reference scans are post-processing methods that require no additional information. One such method (1) minimizes the intensity in a ROI selected in the ghost area by iteratively refining phase parameters. In general, however, this method requires user interaction. Another elegant method (2) uses the total image entropy as a cost function for iterative optimization and makes no assumptions about the shape or size of the object being imaged. However, the computation time to correct a 64-slice 128¿128 4-shot data set has been reported to be 2.5 min (2). For this method to be a dependable replacement for the reference scan in the clinic it may never fail, regardless of acquisition parameters chosen, anatomy of interest and how well the system is calibrated. Here we present a robust iterative entropy minimization implementation for ghost removal that we now use routinely as a replacement for reference scanning in clinical single- and multi-shot, GRAPPA-accelerated DWI and PWI EPI exams.

该子项目是利用NIH/NCRR资助的中心赠款提供的资源的许多研究子项目之一。子项目和研究者（PI）可能从另一个NIH来源获得主要资金，因此可以在其他CRISP条目中表示。所列机构为中心，不一定是研究者所在机构。导论.由于奇数和偶数回波之间的未对准，EPI中会出现奈奎斯特重影。出于这个原因，临床EPI扫描通常与结合到预扫描过程中的参考扫描一起执行，其中相位信息可以用于校正重影误差。对于多激发、多线圈和多切片采集，这种额外的扫描通常会超过一分钟，这在例如急性中风的情况下可能是至关重要的。参考扫描的一个有趣的替代方法是不需要额外信息的后处理方法。一种这样的方法（1）通过迭代地细化相位参数来最小化在重影区域中选择的ROI中的强度。然而，一般来说，这种方法需要用户交互。另一种优雅的方法（2）使用总图像熵作为迭代优化的成本函数，并且不对成像对象的形状或大小进行假设。然而，据报道，校正64切片128 ² 128 4次激发数据集的计算时间为2.5分钟（2）。为了使这种方法成为临床中参考扫描的可靠替代品，无论选择的采集参数、感兴趣的解剖结构以及系统校准的程度如何，它都不会失败。在这里，我们提出了一个强大的迭代熵最小化实现重影去除，我们现在使用常规的替代参考扫描在临床单次和多次拍摄，GRAPPA加速DWI和PWI EPI检查。