Accurate catheter tracking is crucial during minimally invasive endovascular
procedures (MIEP), and electromagnetic (EM) tracking is a widely used
technology that serves this purpose. However, registration between preoperative
images and the EM tracking system is often challenging. Existing registration
methods typically require manual interactions, which can be time-consuming,
increase the risk of errors and change the procedural workflow. Although
several registration methods are available for catheter tracking, such as
marker-based and path-based approaches, their limitations can impact the
accuracy of the resulting tracking solution, consequently, the outcome of the
medical procedure.
This paper introduces a novel automated catheter registration method for
EM-guided MIEP. The method utilizes 3D signal temporal analysis, such as
Dynamic Time Warping (DTW) algorithms, to improve registration accuracy and
reliability compared to existing methods. DTW can accurately warp and match
EM-tracked paths to the vessel's centerline, making it particularly suitable
for registration. The introduced registration method is evaluated for accuracy
in a vascular phantom using a marker-based registration as the ground truth.
The results indicate that the DTW method yields accurate and reliable
registration outcomes, with a mean error of $2.22$mm. The introduced
registration method presents several advantages over state-of-the-art methods,
such as high registration accuracy, no initialization required, and increased
automation.

该论文介绍了一种新颖的基于动态时间规整算法的三维序列信号分析的电磁导航下微创血管插管手术的导管注册方法，与现有方法相比，该方法提高了注册的准确性和可靠性，并且具有高精度、无需初始化和增加自动化等优点。

WarpEM：EM 指导程序中用于精确导管配准的动态时间扭曲

WarpEM: Dynamic Time Warping for Accurate Catheter Registration in  EM-guided Procedures

Device tracking is an important prerequisite for guidance during endovascular
procedures. Especially during cardiac interventions, detection and tracking of
guiding the catheter tip in 2D fluoroscopic images is important for
applications such as mapping vessels from angiography (high dose with contrast)
to fluoroscopy (low dose without contrast). Tracking the catheter tip poses
different challenges: the tip can be occluded by contrast during angiography or
interventional devices; and it is always in continuous movement due to the
cardiac and respiratory motions. To overcome these challenges, we propose
ConTrack, a transformer-based network that uses both spatial and temporal
contextual information for accurate device detection and tracking in both X-ray
fluoroscopy and angiography. The spatial information comes from the template
frames and the segmentation module: the template frames define the surroundings
of the device, whereas the segmentation module detects the entire device to
bring more context for the tip prediction. Using multiple templates makes the
model more robust to the change in appearance of the device when it is occluded
by the contrast agent. The flow information computed on the segmented catheter
mask between the current and the previous frame helps in further refining the
prediction by compensating for the respiratory and cardiac motions. The
experiments show that our method achieves 45% or higher accuracy in detection
and tracking when compared to state-of-the-art tracking models.

提出了一种基于转换器的网络 ConTrack，利用空间和时间上下文信息在 X 光荧光和描记术图像中进行准确的设备检测和跟踪。