浙江大学学报(工学版)  2021, Vol. 55 Issue (12): 2373-2381    DOI: 10.3785/j.issn.1008-973X.2021.12.018
 电子、通信与自动控制技术

1. 兰州理工大学 电气工程与信息工程学院，甘肃 兰州 730050
2. 兰州理工大学 甘肃省工业过程先进控制重点实验室，甘肃 兰州 730050
3. 兰州理工大学 国家级电气与控制工程实验教学中心，甘肃 兰州 730050
3D model fitting method based on point distribution model
Zhu-ye XU1(),Xiao-qiang ZHAO1,2,3,*(),Hong-mei JIANG1,2,3
1. College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China
2. Key Laboratory of Gansu Advanced Control for Industrial Process, Lanzhou University of Technology, Lanzhou 730050, China
3. National Experimental Teaching Center of Electrical and Control Engineering, Lanzhou University of Technology, Lanzhou 730050, China
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Abstract:

A 3D model fitting method based on point distribution model (3DMFB-PDM) was proposed, aiming at the problem of poor fitting between the 3D anatomical structure model of the patient’s part constructed by the traditional method and the test samples. Firstly, the data processing was performed on the training sample set to align the template sample with the target sample, and the adverse effects of training sample due to rotation and scale changes were alleviated. Then the correspondence among training samples was established, and the patient’s point distribution model with a normal distribution was represented. Finally, the distance between the feature point and the corresponding point in the point distribution model was calculated. By introducing the Mahalanobis distance and converting the nonlinear equations were to minimize the distance. Meanwhile, the shape parameters of the point distribution model were continuously adjusted according to the minimum distance, thus the point distribution model was fitted to the test samples. 30 groups of left femurs were selected as the training sample set for experimental verification to verify the effectiveness of 3DMFB-PDM. Results show that the fitting error after introducing additional terms is smaller than the fitting error without introducing additional terms. Comparing 3DMFB-PDM with the other three methods shows that the fitting error of 3DMFB-PDM is the smallest, which indicate that 3DMFB-PDM can effectively fit the 3D anatomical structure model of the patient’s part to the test samples.

Key words: medical image processing    3D modeling    shape analysis    point distribution model    Mahalanobis distance

 CLC: TP 391.41

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#### 引用本文:

Zhu-ye XU,Xiao-qiang ZHAO,Hong-mei JIANG. 3D model fitting method based on point distribution model. Journal of ZheJiang University (Engineering Science), 2021, 55(12): 2373-2381.

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 图 1  3DMFB-PDM的建模与拟合流程图 图 2  30组左侧股骨的3D模型 表 1  30组左侧股骨图像的人体测量学信息 图 3  模板样本的可视化结果 图 4  模板样本的点云表示 图 5  训练样本的点分布模型 图 6  特征向量表征变形模型的百分比 表 2  未引入附加项与引入附加项的误差比较 表 3  点分布模型与多个测试样本的误差比较 表 4  不同方法构建点分布模型的时间对比 表 5  4种方法的误差比较 表 6  4种方法在3个测试样本下的拟合误差 图 7  4种方法构建的点分布模型的模型性能对比
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