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飞行时间相机、光学跟踪器和计算机断层扫描在成对数据配准中的应用

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration.

作者信息

Pycinski Bartlomiej, Czajkowska Joanna, Badura Pawel, Juszczyk Jan, Pietka Ewa

机构信息

Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland.

出版信息

PLoS One. 2016 Jul 19;11(7):e0159493. doi: 10.1371/journal.pone.0159493. eCollection 2016.

Abstract

PURPOSE

A growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed.

METHODS

We present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm.

RESULTS

The experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera.

CONCLUSION

The obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers.

摘要

目的

包括微创手术在内,越来越多的医学应用依赖于多模态或多传感器数据处理。快速准确的三维场景分析,包括数据配准,对于计算机辅助诊断和治疗的发展似乎至关重要。基于光学跟踪器的表面跟踪系统的进步已经在手术规划中发挥了重要作用。然而,在非医学领域广泛探索的新模态,如飞行时间(ToF)传感器,功能强大,有潜力成为计算机辅助手术设置的一部分。不同采集系统的连接有望为手术室程序提供有价值的支持。因此,需要对这种多传感器定位系统的精度进行详细分析。

方法

我们展示了一种将术前CT序列与术中ToF传感器和光学跟踪器点云相结合的系统。该方法包括:光学传感器设置和ToF相机校准程序、数据预处理算法和配准技术。数据预处理在CT的情况下生成一个表面,以及ToF传感器的点云和感兴趣对象的标记驱动光学跟踪器表示。应用的配准技术基于迭代最近点算法。

结果

实验在豪斯多夫距离和平均绝对距离度量方面验证了涉及四种不同人体器官模型的每对模态/传感器的配准。CT和光学跟踪器组合获得了最佳的表面对齐,而涉及ToF相机的实验最差。

结论

所获得的精度鼓励进一步开发多传感器系统。所提出的关于系统局限性和可能改进的实质性讨论,主要与ToF传感器产生的深度信息有关,对计算机辅助手术开发者很有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f414/4951045/defd7599897f/pone.0159493.g001.jpg

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