IEEE Trans Med Imaging. 2013 Oct;32(10):1745-64. doi: 10.1109/TMI.2013.2263152. Epub 2013 May 15.
The paper presents a new endoscope motion tracking method that is based on a novel external endoscope tracking device and our modified stochastic optimization method for boosting endoscopy navigation. We designed a novel tracking prototype where a 2-D motion sensor was introduced to directly measure the insertion-retreat linear motion and also the rotation of the endoscope. With our developed stochastic optimization method, which embeds traceable particle swarm optimization in the Condensation algorithm, a full six degrees-of-freedom endoscope pose (position and orientation) can be recovered from 2-D motion sensor measurements. Experiments were performed on a dynamic bronchial phantom with maximal simulated respiratory motion around 24.0 mm. The experimental results demonstrate that our proposed method provides a promising endoscope motion tracking approach with more effective and robust performance than several current available tracking techniques. The average tracking accuracy of the position improved from 6.5 to 3.3 mm, which further approaches the clinical requirement of 2.0 mm in practice.
本文提出了一种新的内窥镜运动跟踪方法,该方法基于新型的外部内窥镜跟踪设备和我们改进的随机优化方法,以增强内窥镜导航。我们设计了一种新型的跟踪原型,其中引入了一个 2D 运动传感器,以直接测量插入-退出的直线运动以及内窥镜的旋转。通过我们开发的随机优化方法,将可追踪的粒子群优化嵌入到 Condensation 算法中,可以从 2D 运动传感器测量中恢复出完整的六自由度内窥镜姿态(位置和方向)。在最大模拟呼吸运动约 24.0mm 的动态支气管模型上进行了实验。实验结果表明,与几种现有的跟踪技术相比,我们提出的方法提供了一种很有前途的内窥镜运动跟踪方法,具有更有效和更稳健的性能。位置的平均跟踪精度从 6.5 毫米提高到 3.3 毫米,进一步接近实际中 2.0 毫米的临床要求。