Feasibility of differential geometry-based features in detection of anatomical feature points on patient surfaces in range image-guided radiation therapy.
Feasibility of differential geometry-based features in detection of anatomical feature points on patient surfaces in range image-guided radiation therapy.
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基于微分几何的特征在范围图像引导放射治疗中检测患者表面解剖特征点的可行性。
DOI：
10.1007/s11548-016-1436-x
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发表时间：
2016
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影响因子：
--
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et al.
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作者：
Soufi M;Arimura H;Nakamura K;et al.
目的探讨微分几何特征在图像引导放射治疗中红外线距离像中患者体表解剖特征点检测中的可行性。点分布与三维坐标，并描述在每个点的几何形状的曲率特征。利用模板匹配技术提取深度图像上的感兴趣区域，并对深度图像进行了时间和空间降噪处理。然后，利用非均匀有理B样条模型从深度图像重建出患者的数学光滑表面。根据重构曲面的曲率特征提取特征点。该框架进行了测试的范围内获得的飞行时间（TOF）相机和Kinect传感器的两个表面（纹理）类型的头部幻影A和B，具有不同的解剖几何形状的图像。通过测量残差来评价检测精度，即，参考（地面实况）和凸，凹regions.ResultsThe MMED检测到的特征点之间的最小欧几里德距离（MMED）的平均值使用凸特征点的平移和旋转的幻影A的距离图像分别是和，使用TOF相机。对于体模B，使用Kinect传感器时，凸和凹特征点的MMED分别为和mm。有一个统计学上的显着差异，在减少MMED凸特征点相比凹featurepoints.ConclusionsThe建议的框架已经证明了微分几何特征的可行性，在范围内的图像引导放射治疗的患者表面上的解剖特征点的检测。
PurposeTo investigate the feasibility of differential geometry features in the detection of anatomical feature points on a patient surface in infrared-ray-based range images in image-guided radiation therapy.MethodsThe key technology was to reconstruct the patient surface in the range image, i.e., point distribution with three-dimensional coordinates, and characterize the geometrical shape at every point based on curvature features. The region of interest on the range image was extracted by using a template matching technique, and the range image was processed for reducing temporal and spatial noise. Next, a mathematical smooth surface of the patient was reconstructed from the range image by using a non-uniform rational B-splines model. The feature points were detected based on curvature features computed on the reconstructed surface. The framework was tested on range images acquired by a time-of-flight (TOF) camera and a Kinect sensor for two surface (texture) types of head phantoms A and B that had different anatomical geometries. The detection accuracy was evaluated by measuring the residual error, i.e., the mean of minimum Euclidean distances (MMED) between reference (ground truth) and detected feature points on convex and concave regions.ResultsThe MMEDs obtained using convex feature points for range images of the translated and rotated phantom A wereand, respectively, using the TOF camera. For the phantom B, the MMEDs of the convex and concave feature points wereandmm, respectively, using the Kinect sensor. There was a statistically significant difference in the decreased MMED for convex feature points compared with concave feature points.ConclusionsThe proposed framework has demonstrated the feasibility of differential geometry features for the detection of anatomical feature points on a patient surface in range image-guided radiation therapy.