• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Ultrasonics, Ferroelectrics and Frequency Control, IEEE Transactions on >A low-complexity data-dependent beamformer
【24h】

A low-complexity data-dependent beamformer

机译：低复杂度的数据相关波束形成器

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

The classical problem of choosing apodization functions for a beamformer involves a trade-off between main lobe width and side lobe level, i.e., a trade-off between resolution and contrast. To avoid this trade-off, the application of adaptive beamforming, such as minimum variance beamforming, to medical ultrasound imaging has been suggested. This has been an active topic of research in medical ultrasound imaging in the recent years, and several authors have demonstrated significant improvements in image resolution. However, the improvement comes at a considerable cost. Where the complexity of a conventional beamformer is linear with the number of elements [O(M)], the complexity of a minimum variance beamformer is as high as O(M3). In this paper, we have applied a method based on an idea by Vignon and Burcher which is data-adaptive, but selects the apodization function between several predefined windows, giving linear complexity. In the proposed method, we select an apodization function for each depth along a scan line based on the optimality criterion of the minimum variance beamformer. However, unlike the minimum variance beamformer, which has an infinite solution space, we limit the number of possible outcomes to a set of predefined windows. The complexity of the method is then only P times that of the conventional method, where P is the number of predefined windows. The suggested method gives significant improvement in image resolution at a low cost. The method is robust, can handle coherent targets, and is easy to implement. It may also be used as a classifier because the selected window gives information about the object being imaged. We have applied the method to simulated data of wire targets and a cyst phantom, and to experimental RF data from a heart phantom using P = 4 and P = 12. The results show significant improvement in image resolution compared with delay-and-sum.
机译：为波束形成器选择变迹函数的经典问题涉及主瓣宽度和旁瓣水平之间的折衷，即，分辨率和对比度之间的折衷。为了避免这种折衷，已经建议将自适应波束形成（例如最小方差波束形成）应用于医学超声成像。近年来，这一直是医学超声成像研究的一个活跃主题，几位作者已经证明了图像分辨率的显着提高。但是，这种改进付出了可观的代价。在常规波束形成器的复杂度与元素[O（M）]呈线性关系的情况下，最小方差波束形成器的复杂度高达O（M3）。在本文中，我们应用了基于Vignon和Burcher的思想的方法，该方法具有数据自适应性，但是在多个预定义窗口之间选择切趾函数，从而给出了线性复杂度。在提出的方法中，我们基于最小方差波束形成器的最佳准则为沿着扫描线的每个深度选择切趾函数。但是，与具有无限求解空间的最小方差波束形成器不同，我们将可能结果的数量限制为一组预定义的窗口。那么该方法的复杂度仅为传统方法的P倍，其中P是预定义窗口的数量。所提出的方法以低成本显着改善了图像分辨率。该方法是鲁棒的，可以处理相干的目标，并且易于实现。它也可以用作分类器，因为选定的窗口会提供有关要成像的对象的信息。我们已将该方法应用于导线目标和囊肿体模的模拟数据，以及使用P = 4和P = 12的来自心脏体模的实验RF数据。结果表明，与延迟总和相比，图像分辨率有了显着提高。

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