Department of Neurosurgery, Neuroscience, & Radiosurgery Hybrid Research Center, Inje University Ilsan Paik Hospital, College of Medicine, Goyang, Republic of Korea.
Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
J Appl Clin Med Phys. 2022 Mar;23(3):e13521. doi: 10.1002/acm2.13521. Epub 2022 Jan 5.
To evaluate a feasibility of normal distribution transform (NDT) algorithm compared with the iterative closest point (ICP) method as a useful surface registration in stereotactic body radiotherapy (SBRT)/stereotactic radiosurgery (SRS).
Point cloud images using the 3D triangulation technology were obtained from a depth camera-based optical imaging (OSI) system equipped in a radiosurgery room. Two surface registration algorithms, NDT and ICP, were used to measure and compare the discrepancy values between the reference and the current surfaces during the positioning of the patient. The performance evaluation was investigated by calculating the registration error and root-mean-square (RMS) values for the surface model, reposition, and target accuracy, which were analyzed statistically using a paired t-test.
For surface model accuracy, the average of the registration error and RMS values were measured as 3.56 ± 2.20 mm and 6.98 ± 1.89 mm for ICP method, and 1.76 ± 1.32 mm and 3.58 ± 1.30 mm for NDT method (p < 0.05). For reposition accuracy, the average registration error and RMS values were calculated as 1.41 ± 0.98 mm and 2.53 ± 1.64 mm using ICP method, and 0.92 ± 0.61 mm and 1.75 ± 0.80 mm using NDT method (p = 0.005). The overall target accuracy using the NDT method reduced the average of the reposition error and overall RMS value by 0.71 and 1.32 mm, respectively, compared to the ICP method (p = 0.03).
We found that the surface registration algorithm based on NDT method provides more reliable accuracy in the values of surface model, reposition, and target accuracies than the classic ICP method. The NDT method in OSI systems offers reasonable accuracy in SBRT/SRS.
评估正态分布变换（NDT）算法与迭代最近点（ICP）方法作为立体定向体放射治疗（SBRT）/立体定向放射外科（SRS）中有用的表面配准方法的可行性。
使用基于深度相机的光学成像（OSI）系统获得 3D 三角测量技术的点云图像，该系统安装在放射外科室中。使用两种表面配准算法，NDT 和 ICP，在患者定位过程中测量和比较参考表面和当前表面之间的差异值。通过计算表面模型、重新定位和目标精度的配准误差和均方根（RMS）值来评估性能，并使用配对 t 检验进行统计分析。
对于表面模型精度，ICP 方法的平均配准误差和 RMS 值分别为 3.56 ± 2.20mm 和 6.98 ± 1.89mm，NDT 方法分别为 1.76 ± 1.32mm 和 3.58 ± 1.30mm（p<0.05）。对于重新定位精度，ICP 方法的平均配准误差和 RMS 值分别为 1.41 ± 0.98mm 和 2.53 ± 1.64mm，NDT 方法分别为 0.92 ± 0.61mm 和 1.75 ± 0.80mm（p=0.005）。与 ICP 方法相比，NDT 方法在整体目标精度方面，重新定位误差和整体 RMS 值的平均值分别降低了 0.71 和 1.32mm（p=0.03）。
我们发现，基于 NDT 方法的表面配准算法在表面模型、重新定位和目标精度的数值方面提供了更可靠的准确性，优于经典的 ICP 方法。OSI 系统中的 NDT 方法在 SBRT/SRS 中具有合理的准确性。
