Purpose

Due to the complex anatomical structure of bronchi and the resembling inner surfaces of airway lumina, bronchoscopic examinations require additional 3D navigational information to assist the physicians. A bronchoscopic navigation system provides the position of the endoscope in CT images with augmented anatomical information. To overcome the shortcomings of previous navigation systems, we propose using a technique known as visual simultaneous localization and mapping (SLAM) to improve bronchoscope tracking in navigation systems.

Methods

We propose an improved version of the visual SLAM algorithm and use it to estimate nt-specific bronchoscopic video as input. We improve the tracking procedure by adding more narrow criteria in feature matching to avoid mismatches. For validation, we collected several trials of bronchoscopic videos with a bronchoscope camera by exploring synthetic rubber bronchus phantoms. We simulated breath by adding periodic force to deform the phantom. We compared the camera positions from visual SLAM with the manually created ground truth of the camera pose. The number of successfully tracked frames was also compared between the original SLAM and the proposed method.

Results

We successfully tracked 29,559 frames at a speed of 80 ms per frame. This corresponds to 78.1% of all acquired frames. The average root mean square error for our technique was 3.02 mm, while that for the original was 3.61 mm.

Conclusion

We present a novel methodology using visual SLAM for bronchoscope tracking. Our experimental results showed that it is feasible to use visual SLAM for the estimation of the bronchoscope camera pose during bronchoscopic navigation. Our proposed method tracked more frames and showed higher accuracy than the original technique did. Future work will include combining the tracking results with virtual bronchoscopy and validation with in vivo cases.

中文翻译：

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基于视觉SLAM的支气管镜导航方案，用于支气管镜导航。

目的

由于支气管的复杂解剖结构和气道腔的内表面相似，支气管镜检查需要附加的3D导航信息来协助医师。支气管镜导航系统为内窥镜在CT图像中的位置提供了增强的解剖信息。为了克服以前的导航系统的缺点，我们建议使用一种称为可视同时定位和地图绘制（SLAM）的技术来改善导航系统中的支气管镜跟踪。

方法

我们提出了视觉SLAM算法的改进版本，并使用它来估计特定于nt的支气管镜视频作为输入。我们通过在特征匹配中添加更窄的标准来避免不匹配，从而改进了跟踪过程。为了进行验证，我们通过探索合成橡胶支气管体模，收集了使用支气管镜相机进行的支气管镜视频的多次试验。我们通过增加周期性的力使人体模型变形来模拟呼吸。我们将视觉SLAM中的相机位置与手动创建的相机姿势的地面真实情况进行了比较。还比较了原始SLAM和建议方法之间成功跟踪的帧数。

结果

我们以每帧80毫秒的速度成功跟踪了29,559帧。这相当于所有已采集帧的78.1％。我们的技术的平均均方根误差为3.02 mm，而原始技术的平均均方根误差为3.61 mm。

结论

我们提出了一种使用视觉SLAM进行支气管镜跟踪的新颖方法。我们的实验结果表明，在支气管镜导航过程中使用视觉SLAM估计支气管镜相机姿势是可行的。我们提出的方法可以跟踪更多帧，并且显示出比原始技术更高的准确性。未来的工作将包括将跟踪结果与虚拟支气管镜检查相结合，并针对体内病例进行验证。