• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Magnetic resonance in medicine: official journal of the Society of Magnetic Resonance in Medicine >Using GRAPPA to improve autocalibrated coil sensitivity estimation for the SENSE family of parallel imaging reconstruction algorithms.
【24h】

Using GRAPPA to improve autocalibrated coil sensitivity estimation for the SENSE family of parallel imaging reconstruction algorithms.

机译：使用GRAPPA改善SENSE系列并行成像重建算法的自动校准线圈灵敏度估计。

获取原文
获取原文并翻译 | 示例
       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Two strategies are widely used in parallel MRI to reconstruct subsampled multicoil image data. SENSE and related methods employ explicit receiver coil spatial response estimates to reconstruct an image. In contrast, coil-by-coil methods such as GRAPPA leverage correlations among the acquired multicoil data to reconstruct missing k-space lines. In self-referenced scenarios, both methods employ Nyquist-rate low-frequency k-space data to identify the reconstruction parameters. Because GRAPPA does not require explicit coil sensitivities estimates, it needs considerably fewer autocalibration signals than SENSE. However, SENSE methods allow greater opportunity to control reconstruction quality though regularization and thus may outperform GRAPPA in some imaging scenarios. Here, we employ GRAPPA to improve self-referenced coil sensitivity estimation in SENSE and related methods using very few auto-calibration signals. This enables one to leverage each methods' inherent strength and produce high quality self-referenced SENSE reconstructions.
机译：并行MRI中广泛使用了两种策略来重建欠采样的多线圈图像数据。 SENSE和相关方法采用显式接收器线圈空间响应估计来重建图像。相反，诸如GRAPPA的逐线圈方法利用所获取的多线圈数据之间的相关性来重建缺失的k空间线。在自参考方案中，两种方法都使用奈奎斯特速率低频k空间数据来识别重建参数。由于GRAPPA不需要明确的线圈灵敏度估计，因此与SENSE相比，它需要的自动校准信号要少得多。但是，SENSE方法通过正则化为控制重建质量提供了更大的机会，因此在某些成像场景中可能胜过GRAPPA。在这里，我们采用GRAPPA改进了SENSE和相关方法中使用很少自动校准信号的自参考线圈灵敏度估计。这使人们能够利用每种方法的固有优势，并产生高质量的自参考SENSE重建。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号