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超声采集的声窗规划。

Acoustic window planning for ultrasound acquisition.

机构信息

Computer Aided Medical Procedures, Technische Universität München, Boltzmannstr. 3, 85748, Garching, Germany.

Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA.

出版信息

Int J Comput Assist Radiol Surg. 2017 Jun;12(6):993-1001. doi: 10.1007/s11548-017-1551-3. Epub 2017 Mar 11.

Abstract

UNLABELLED

Autonomous robotic ultrasound has recently gained considerable interest, especially for collaborative applications. Existing methods for acquisition trajectory planning are solely based on geometrical considerations, such as the pose of the transducer with respect to the patient surface.

PURPOSE

This work aims at establishing acoustic window planning to enable autonomous ultrasound acquisitions of anatomies with restricted acoustic windows, such as the liver or the heart.

METHODS

We propose a fully automatic approach for the planning of acquisition trajectories, which only requires information about the target region as well as existing tomographic imaging data, such as X-ray computed tomography. The framework integrates both geometrical and physics-based constraints to estimate the best ultrasound acquisition trajectories with respect to the available acoustic windows. We evaluate the developed method using virtual planning scenarios based on real patient data as well as for real robotic ultrasound acquisitions on a tissue-mimicking phantom.

RESULTS

The proposed method yields superior image quality in comparison with a naive planning approach, while maintaining the necessary coverage of the target.

CONCLUSION

We demonstrate that by taking image formation properties into account acquisition planning methods can outperform naive plannings. Furthermore, we show the need for such planning techniques, since naive approaches are not sufficient as they do not take the expected image quality into account.

摘要

未加标签

自主机器人超声技术最近引起了相当大的兴趣,特别是在协作应用方面。现有的采集轨迹规划方法仅基于几何考虑,例如换能器相对于患者表面的姿势。

目的

本工作旨在建立声窗规划,以实现具有受限声窗的解剖结构的自主超声采集,例如肝脏或心脏。

方法

我们提出了一种全自动的采集轨迹规划方法,仅需要关于目标区域的信息以及现有的层析成像数据,例如 X 射线计算机断层扫描。该框架结合了几何和基于物理的约束条件,以根据可用的声窗来估计最佳的超声采集轨迹。我们使用基于真实患者数据的虚拟规划场景以及在组织模拟体模上的真实机器人超声采集来评估所开发的方法。

结果

与简单的规划方法相比,所提出的方法在保持目标必要覆盖的同时产生了更好的图像质量。

结论

我们证明了通过考虑成象特性,采集规划方法可以优于简单的规划方法。此外,我们还表明了需要这种规划技术,因为简单的方法是不够的,因为它们没有考虑到预期的图像质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9597/5447334/db38eb939f6d/11548_2017_1551_Fig1_HTML.jpg

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