Schlosser J, Kirmizibayrak C, Shamdasani V, Metz S, Hristov D
Stanford University.
Philips Medical.
Med Phys. 2012 Jun;39(6Part3):3617. doi: 10.1118/1.4734685.
In prior work we developed a robotic system providing real-time soft-tissue ultrasound (US) volumes during radiotherapy beam delivery. for image guidance, the US volumes must be transformed to the linear accelerator reference frame. In this work we propose and characterize a new method of calibrating 4D US volumes based on automatic intramodality image registration.
A dynamic navigation link was used to port 3D US volumes from a Philips iU22 xMatrix machine to a PC in real-time. Sixty volumetric (3D) US images of a pelvic phantom were collected from various probe positions while the transducer's pose was monitored by an optical tracking system. US volumes were automatically registered to the first US volume using normalized mutual information. A system of equations was formulated and solved for the US probe-to-image transformation using the registration transformations and the optical tracking information. Accuracy of the US calibration was assessed on eight additional US volumes with two separate methods. In the first method, a set of three fiducial markers implanted in the phantom was manually selected in each volume by three individual readers. Selected marker locations were reconstructed in the stationary camera frame, and for each marker, mean distance to the reconstructed centroid was measured. In the second method, a bladder structure was semi-automatically segmented in each image volume. Mean distance between bladders segmented in a reference volume and the other seven volumes was computed. Calibration accuracy was also investigated as a function of the number of calibration images used.
Mean error for the fiducial marker reconstruction was 2.3 mm. Mean distance error between segmented structures was 1.1 mm. The proposed calibration method typically converged with less than 20 images.
Automatic image registration facilitates fast and simple US spatial calibration with accuracy under 2.3 mm using any US phantom. This work is supported in part by the Stanford University BioX program and by Philips Medical. Two of the authors of the abstract are employed by Philips Medical.
在之前的工作中,我们开发了一种机器人系统,可在放射治疗束输送过程中提供实时软组织超声(US)容积。为了进行图像引导,必须将US容积转换到直线加速器参考坐标系。在这项工作中,我们提出并描述了一种基于自动模态内图像配准来校准4D US容积的新方法。
使用动态导航链接将3D US容积从飞利浦iU22 xMatrix机器实时传输到个人计算机。在通过光学跟踪系统监测换能器姿态的同时,从不同探头位置采集盆腔体模的60幅容积式(3D)US图像。使用归一化互信息将US容积自动配准到第一幅US容积。利用配准变换和光学跟踪信息,建立并求解用于US探头到图像变换的方程组。使用两种不同方法在另外八幅US容积上评估US校准的准确性。在第一种方法中,由三位独立的读者在每个容积中手动选择一组植入体模的三个基准标记。在固定相机坐标系中重建所选标记的位置,并测量每个标记到重建质心的平均距离。在第二种方法中,在每个图像容积中半自动分割膀胱结构。计算在参考容积和其他七个容积中分割的膀胱之间的平均距离。还研究了校准准确性与所用校准图像数量的函数关系。
基准标记重建的平均误差为2.3毫米。分割结构之间平均距离误差为1.1毫米。所提出的校准方法通常在少于20幅图像时收敛。
自动图像配准有助于使用任何US体模快速简单地进行US空间校准,精度低于2.3毫米。这项工作部分得到了斯坦福大学BioX计划和飞利浦医疗公司的支持。摘要的两位作者受雇于飞利浦医疗公司。