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Using Multiple Scanning Devices for 3-D Modeling

机译:使用多种扫描设备进行3-D模型

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Medical applications for 3D printing are expanding rapidly and are expected to revolutionize health care (Hammoudi et al. in Extracting wire-frame models of street facades from 3D point clouds and the corresponding cadastral map, Saint-Mandé, France, pp. 91-96, 2010) [1]. Medical uses for 3D printing, both actual and potential, can be organized into several broad categories, including: tissue and organ fabrication; creation of customized prosthetics, implants, and anatomical models; and pharmaceutical research regarding drug dosage forms, delivery, and discovery (Sitek in IEEE Trans Med Imag 25:1172, 2006) [2]. The application of 3D printing in medicine can provide many benefits, including: the customization and personalization of medical products, drugs, and equipment; cost-effectiveness; increased productivity; the democratization of design and manufacturing; and enhanced collaboration (Bernardini in Comput Graph Forum 21 (2): 149-172, 2002) [3]. Reconstruction of the object from 3D scans can be achieved either by use of sophisticated algorithms (Ozbolat and Yu in IEEE Trans Biomed Eng 60(3):691-699, 2013) [4] or directly from the point clouds (Hoy in Med Ref Serv Q 32(1):94-99, 2013) [5], (3D Print Exchange in National Institutes of Health, 2014) [6]. The second approach has an advantage of much higher speed since no image recognition is necessary. However it may also result in the loss of accuracy. To speed-up the scanning procedure we propose use of multiple scanners to obtain a point cloud of a given object. A few mathematical problems will arise with this approach. The most important among them is the calibration of multiple scanners. It is considered in the paper. We propose mathematical formulation of the calibration problem and give a linear time complexity algorithm to approximately solve this problem. The other problems including the study of how the measurement errors propagate to the errors of the image and how to recalculate point clouds from different scanner, is the subject of our current research and are not considered in the paper.
机译:3D打印的医疗应用正在迅速扩展,预计将彻底改变医疗保健(Hammoudi等人。在从3D点云和相应的地籍地图中提取街道外观的线框模型,法国Saint-Mandé,PP。91-96 ,2010)[1]。用于3D打印的医疗用途,实际和潜力都可以组织成几种广泛类别,包括:组织和器官制作;创建定制的假肢,植入物和解剖模型;关于药物剂型,递送和发现的药物研究(IEEE Transm Med Impt 25:1172,2006)[2]。 3D打印在医学中的应用可以提供许多好处,包括:医疗产品,药物和设备的定制和个性化;成本效益;提高生产力;设计与制造的民主化;加强协作(Bernardini在计算图论坛21(2):149-172,2002)[3]。通过使用复杂的算法(IEEE Trans Biomed Eng 60(3)中的ozbolat和yu)或直接来自点云(MED REF中的HOY Serv Q 32(1):94-99,2013)[5],(3D在国家健康机构中的印刷交换,2014)[6]。由于不需要图像识别,第二方法具有更高的速度优点。然而,它也可能导致准确性损失。加快扫描过程,我们建议使用多个扫描仪来获取给定对象的点云。这种方法会出现一些数学问题。其中最重要的是多个扫描仪的校准。它在纸上被考虑。我们提出了校准问题的数学制定,并提供了线性时间复杂度算法大致解决了这个问题。其他问题包括研究测量误差如何传播到图像的错误以及如何从不同扫描仪重新计算点云,是我们当前研究的主题,并在论文中被考虑。

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