Automatic 3D ultrasound calibration for image guided therapy using intramodality image registration.

Automatic 3D ultrasound calibration for image guided therapy using intramodality image registration.
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DOI:
10.1088/0031-9155/58/21/7481
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发表时间:
2013-11-07
影响因子:
3.5
通讯作者:
Hristov D
Hristov D
中科院分区:
工程技术2区
文献类型:
--
作者:
Schlosser J;Kirmizibayrak C;Shamdasani V;Metz S;Hristov D

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许多真实的超声(US)引导的治疗可以受益于相对于先前采集的计算机化解剖模型的运动诱导的解剖变化的管理。空间校准是将US图像信息转换到解剖模型的参考系的先决条件。我们提出了一种新的方法,用于校准三维超声体积使用intramodality图像配准,来自“手眼”校准技术。该方法是完全自动化的,通过实施数据拒绝基于传感器位移,自动注册重叠的图像区域,并在校准过程中连续评估的自一致性误差度量。我们还提出了一种新的方法,用于验证美国校准的基础上测量的物理体模位移在美国的图像。校准和验证都可以在任意体模上执行。结果表明,归一化互信息和局部互相关产生最准确的三维超声配准校准。体积图像对齐比用于验证校准的点选择更准确和可再现,产生<1.5 mm的均方根误差,相对于先前报告的手眼US校准结果有显著改进。比较两种不同的体模用于校准和验证,结果显示验证存在显著差异(p=0.003),但校准无显著差异(p=0.795)。
Many real time ultrasound (US) guided therapies can benefit from management of motion-induced anatomical changes with respect to a previously acquired computerized anatomy model. Spatial calibration is a prerequisite to transforming US image information to the reference frame of the anatomy model. We present a new method for calibrating 3D US volumes using intramodality image registration, derived from the “hand eye” calibration technique. The method is fully automated by implementing data rejection based on sensor displacements, automatic registration over overlapping image regions, and a self-consistency error metric evaluated continuously during calibration. We also present a novel method for validating US calibrations based on measurement of physical phantom displacements within US images. Both calibration and validation can be performed on arbitrary phantoms. Results indicate that normalized mutual information and localized cross correlation produce the most accurate 3D US registrations for calibration. Volumetric image alignment is more accurate and reproducible than point selection for validating the calibrations, yielding <1.5 mm root mean square error, a significant improvement relative to previously reported hand eye US calibration results. Comparison of two different phantoms for calibration and for validation revealed significant differences for validation (p=0.003) but not for calibration (p=0.795).
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