Wagner Martin, Schafer Sebastian, Strother Charles, Mistretta Charles
Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin 53705.
Siemens Medical Solutions USA, Hoffman Estates, Illinois 60192.
Med Phys. 2016 Mar;43(3):1324-34. doi: 10.1118/1.4941950.
Biplane angiography systems provide time resolved 2D fluoroscopic images from two different angles, which can be used for the positioning of interventional devices such as guidewires and catheters. The purpose of this work is to provide a novel algorithm framework, which allows the 3D reconstruction of these curvilinear devices from the 2D projection images for each time frame. This would allow creating virtual projection images from arbitrary view angles without changing the position of the gantries, as well as virtual endoscopic 3D renderings.
The first frame of each time sequence is registered to and subtracted from the following frame using an elastic grid registration technique. The images are then preprocessed by a noise reduction algorithm using directional adaptive filter kernels and a ridgeness filter that emphasizes curvilinear structures. A threshold based segmentation of the device is then performed, followed by a flux driven topology preserving thinning algorithm to extract the segments of the device centerline. The exact device path is determined using Dijkstra's algorithm to minimize the curvature and distance between adjacent segments as well as the difference to the device path of the previous frame. The 3D device centerline is then reconstructed using epipolar geometry.
The accuracy of the reconstruction was measured in a vascular head phantom as well as in a cadaver head and a canine study. The device reconstructions are compared to rotational 3D acquisitions. In the phantom experiments, an average device tip accuracy of 0.35 ± 0.09 mm, a Hausdorff distance of 0.65 ± 0.32 mm, and a mean device distance of 0.54 ± 0.33 mm were achieved. In the cadaver head and canine experiments, the device tip was reconstructed with an average accuracy of 0.26 ± 0.20 mm, a Hausdorff distance of 0.62 ± 0.08 mm, and a mean device distance of 0.41 ± 0.08 mm. Additionally, retrospective reconstruction results of real patient data are presented.
The presented algorithm is a novel approach for the time resolved 3D reconstruction of interventional devices from biplane fluoroscopic images, thus allowing the creation of virtual projection images from arbitrary view angles as well as virtual endoscopic 3D renderings. Availability of this technique would enhance the ability to accurately position devices in minimally invasive endovascular procedures.
双平面血管造影系统可从两个不同角度提供时间分辨的二维荧光透视图像，可用于导丝和导管等介入设备的定位。本研究的目的是提供一种新颖的算法框架，该框架能够从每个时间帧的二维投影图像中重建这些曲线形设备的三维模型。这将允许在不改变龙门架位置的情况下从任意视角创建虚拟投影图像，以及进行虚拟内窥镜三维渲染。
使用弹性网格配准技术将每个时间序列的第一帧与后续帧进行配准并相减。然后使用方向自适应滤波器内核和强调曲线结构的脊线滤波器的降噪算法对图像进行预处理。接着对设备进行基于阈值的分割，随后采用通量驱动的拓扑保持细化算法来提取设备中心线的线段。使用迪杰斯特拉算法确定精确的设备路径，以最小化相邻线段之间的曲率和距离以及与前一帧设备路径的差异。然后使用对极几何重建三维设备中心线。
在血管头部模型、尸体头部和犬类研究中测量了重建的准确性。将设备重建结果与旋转三维采集结果进行比较。在模型实验中，设备尖端平均精度为0.35±0.09毫米，豪斯多夫距离为0.65±0.32毫米，设备平均距离为0.54±0.33毫米。在尸体头部和犬类实验中，设备尖端重建的平均精度为0.26±0.20毫米，豪斯多夫距离为0.62±0.08毫米，设备平均距离为0.41±0.08毫米。此外，还展示了真实患者数据的回顾性重建结果。
所提出的算法是一种从双平面荧光透视图像中对介入设备进行时间分辨三维重建的新方法，从而允许从任意视角创建虚拟投影图像以及进行虚拟内窥镜三维渲染。该技术的可用性将提高在微创血管内手术中准确定位设备的能力。
