Interactive CT-video registration for the continuous guidance of bronchoscopy.
Interactive CT-video registration for the continuous guidance of bronchoscopy.
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DOI：
10.1109/tmi.2013.2252361
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发表时间：
2013-08
影响因子：
10.6
通讯作者：
Higgins WE
中科院分区：
文献类型：
--
作者：
Merritt SA;Khare R;Bascom R;Higgins WE
支气管镜检查是肺癌分期的一个重要步骤。为了进行支气管镜检查，医生使用源自患者 3D 计算机断层扫描 (CT) 胸部扫描的手术计划来引导支气管镜穿过肺部气道。不幸的是，医生进行支气管镜检查的能力差异很大。因此，借鉴基于 CT 的虚拟支气管镜检查 (VB) 概念，提出了图像引导支气管镜检查系统。这些系统试图将支气管镜在胸部的实时位置记录到基于 CT 的虚拟胸部空间。最近的方法将支气管镜视频配准到基于 CT 的腔内气道渲染，显示出希望，但无法实现连续的实时指导。我们提出了一种 CT 视频配准方法，其灵感来自于图像对齐和基于图像的渲染领域的计算机视觉创新。特别是，在 Lucas-Kanade 算法的推动下，我们提出了一个围绕基于梯度的优化过程构建的逆组合框架。接下来，我们提出了一种适用于图像引导支气管镜检查的框架的实现。涉及单帧和连续视频序列的实验室测试证明了该方法的稳健性和准确性。基准计时测试表明，该方法可以以 300 帧/秒的速度连续运行，远远超出实时支气管镜视频的 30 帧/秒的速率。这与其他方法 ≥1 s/帧的速度相比非常有利，表明该方法具有实时连续配准的潜力。一项人体模型研究证实了该方法在受控环境中实时引导的有效性，因此为图像引导支气管镜检查的第一个交互式 CT 视频配准方法指明了道路。沿着这个思路，我们通过一项涉及肺癌患者的临床研究证明了该方法在完整指导系统中的功效。
Bronchoscopy is a major step in lung cancer staging. To perform bronchoscopy, the physician uses a procedure plan, derived from a patient’s 3D computed-tomography (CT) chest scan, to navigate the bronchoscope through the lung airways. Unfortunately, physicians vary greatly in their ability to perform bronchoscopy. As a result, image-guided bronchoscopy systems, drawing upon the concept of CT-based virtual bronchoscopy (VB), have been proposed. These systems attempt to register the bronchoscope’s live position within the chest to a CT-based virtual chest space. Recent methods, which register the bronchoscopic video to CT-based endoluminal airway renderings, show promise but do not enable continuous real-time guidance. We present a CT-video registration method inspired by computer-vision innovations in the fields of image alignment and image-based rendering. In particular, motivated by the Lucas–Kanade algorithm, we propose an inverse-compositional framework built around a gradient-based optimization procedure. We next propose an implementation of the framework suitable for image-guided bronchoscopy. Laboratory tests, involving both single frames and continuous video sequences, demonstrate the robustness and accuracy of the method. Benchmark timing tests indicate that the method can run continuously at 300 frames/s, well beyond the real-time bronchoscopic video rate of 30 frames/s. This compares extremely favorably to the ≥1 s/frame speeds of other methods and indicates the method’s potential for real-time continuous registration. A human phantom study confirms the method’s efficacy for real-time guidance in a controlled setting, and, hence, points the way toward the first interactive CT-video registration approach for image-guided bronchoscopy. Along this line, we demonstrate the method’s efficacy in a complete guidance system by presenting a clinical study involving lung cancer patients.