Ayvali Elif, Desai Jaydev P
Robotics, Automation and Medical Systems (RAMS) Laboratory, Maryland Robotics Center, Institute for Systems Research, University of Maryland, College Park, MD, USA,
Ann Biomed Eng. 2015 Aug;43(8):1828-40. doi: 10.1007/s10439-014-1208-0. Epub 2014 Dec 12.
Image-guided interventions have become the standard of care for needle-based procedures. The success of the image-guided procedures depends on the ability to precisely locate and track the needle. This work is primarily focused on 2D ultrasound-based tracking of a hollow needle (cannula) that is composed of straight segments connected by shape memory alloy actuators. An in-plane tracking algorithm based on optical flow was proposed to track the cannula configuration in real-time. Optical flow is a robust tracking algorithm that can easily run on a CPU. However, the algorithm does not perform well when it is applied to the ultrasound images directly due to the intensity variation in the images. The method presented in this work enables using the optical flow algorithm on ultrasound images to track features of the needle. By taking advantage of the bevel tip, Circular Hough transform was used to accurately locate the needle tip when the imaging is out-of-plane. Through experiments inside tissue phantom and ex-vivo experiments in bovine kidney, the success of the proposed tracking methods were demonstrated. Using the methods presented in this work, quantitative information about the needle configuration is obtained in real-time which is crucial for generating control inputs for the needle and automating the needle insertion.
图像引导介入已成为基于针的手术的护理标准。图像引导手术的成功取决于精确定位和跟踪针的能力。这项工作主要集中在基于二维超声的空心针(套管)跟踪上,该空心针由形状记忆合金致动器连接的直线段组成。提出了一种基于光流的平面内跟踪算法,以实时跟踪套管的形态。光流是一种强大的跟踪算法,可以很容易地在CPU上运行。然而,由于图像中的强度变化,该算法直接应用于超声图像时效果不佳。本文提出的方法能够在超声图像上使用光流算法来跟踪针的特征。利用斜面尖端,当成像为平面外时,使用圆形霍夫变换来精确定位针尖。通过组织模型内的实验和牛肾的离体实验,证明了所提出跟踪方法的成功。使用本文提出的方法,可以实时获得有关针形态的定量信息,这对于生成针的控制输入和使针插入自动化至关重要。