Markerless real-time 3-D target region tracking by motion backprojection from projection images
Markerless real-time 3-D target region tracking by motion backprojection from projection images
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DOI：
10.1109/tmi.2005.857651
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发表时间：
2005-11-01
影响因子：
10.6
通讯作者：
Maurer, CR
中科院分区：
文献类型：
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作者：
Rohlfing, T;Denzler, J;Maurer, CR
患者体内预定义目标区域的准确和快速定位是许多图像引导治疗程序的重要组成部分。这个问题通常通过将术中2-D投影图像配准到3-D术前图像来解决。如果患者在介入过程中没有固定，则在手术过程中重复多次2-D图像采集，并且配准问题可以被转换为3-D跟踪问题。为了解决3-D的问题，我们建议在本文中应用2-D区域跟踪，首先恢复的组件的变换是在平面上的投影。所有投影的2-D运动估计被反向投影到3-D空间中，在那里它们然后被组合成3-D运动的一致估计。我们将此方法与基于强度的2-D到3-D配准以及2-D运动反投影随后的2-D到3-D配准阶段的组合进行比较。使用基于基准标记的金标准变换的临床数据，我们证明了我们的方法能够从X射线投影图像中测量的2-D运动中准确地跟踪3-D中的椎骨目标。使用标准跟踪算法（超平面跟踪），以视频帧速率实现跟踪，但相对经常失败（32%的跟踪帧的目标配准误差（TRE）优于1.2 mm，82%的跟踪帧的TRE优于2.4 mm）。通过使用归一化互信息（NMI）和图案强度（PI）的基于强度的2-D到2-D图像配准，准确性和鲁棒性得到显著提高。NMI跟踪了我们数据中82%的TRE优于1.2 mm的帧和96%的TRE优于2.4 mm的帧。这是以降低帧速率、每帧1.7 s平均处理时间和投影设备为代价的。使用PI的结果稍微更准确，但平均每帧需要5.4秒的时间。这些结果仍然比2-D到3-D配准快得多。我们的结论是，运动反投影从2-D运动跟踪是一个准确和有效的方法跟踪3-D目标运动，但跟踪2-D运动的准确性和鲁棒性仍然是一个挑战。
Accurate and fast localization of a predefined target region inside the patient is an important component of many image-guided therapy procedures. This problem is commonly solved by registration of intraoperative 2-D projection images to 3-D preoperative images. If the patient is not fixed during the intervention, the 2-D image acquisition is repeated several times during the procedure, and the registration problem can be cast instead as a 3-D tracking problem. To solve the 3-D problem, we propose in this paper to apply 2-D region tracking to first recover the components of the transformation that are in-plane to the projections. The 2-D motion estimates of all projections are backprojected into 3-D space, where they are then combined into a consistent estimate of the 3-D motion. We compare this method to intensity-based 2-D to 3-D registration and a combination of 2-D motion backprojection followed by a 2-D to 3-D registration stage. Using clinical data with a fiducial marker-based gold-standard transformation, we show that our method is capable of accurately tracking vertebral targets in 3-D from 2-D motion measured in X-ray projection images. Using a standard tracking algorithm (hyperplane tracking), tracking is achieved at video frame rates but fails relatively often (32% of all frames tracked with target registration error (TRE) better than 1.2 mm, 82% of all frames tracked with TRE better than 2.4 mm). With intensity-based 2-D to 2-D image registration using normalized mutual information (NMI) and pattern intensity (PI), accuracy and robustness are substantially improved. NMI tracked 82% of all frames in our data with TRE better than 1.2 mm and 96% of all frames with TRE better than 2.4 mm. This comes at the cost of a reduced frame rate, 1.7 s average processing time per frame and projection device. Results using PI were slightly more accurate, but required on average 5.4 s time per frame. These results are still substantially faster than 2-D to 3-D registration. We conclude that motion backprojection from 2-D motion tracking is an accurate and efficient method for tracking 3-D target motion, but tracking 2-D motion accurately and robustly remains a challenge.