Novotny Paul M, Stoll Jeff A, Vasilyev Nikolay V, del Nido Pedro J, Dupont Pierre E, Zickler Todd E, Howe Robert D
School of Engineering and Applied Sciences, Harvard University, 29 Oxford Street, Cambridge, MA 02138, USA.
Med Image Anal. 2007 Oct;11(5):458-64. doi: 10.1016/j.media.2007.06.009. Epub 2007 Jul 5.
Real-time three-dimensional ultrasound enables new intracardiac surgical procedures, but the distorted appearance of instruments in ultrasound poses a challenge to surgeons. This paper presents a detection technique that identifies the position of the instrument within the ultrasound volume. The algorithm uses a form of the generalized Radon transform to search for long straight objects in the ultrasound image, a feature characteristic of instruments and not found in cardiac tissue. When combined with passive markers placed on the instrument shaft, the full position and orientation of the instrument is found in 3D space. This detection technique is amenable to rapid execution on the current generation of personal computer graphics processor units (GPU). Our GPU implementation detected a surgical instrument in 31 ms, sufficient for real-time tracking at the 25 volumes per second rate of the ultrasound machine. A water tank experiment found instrument orientation errors of 1.1 degrees and tip position errors of less than 1.8mm. Finally, an in vivo study demonstrated successful instrument tracking inside a beating porcine heart.
实时三维超声使新型心内手术成为可能,但超声中器械的变形外观给外科医生带来了挑战。本文提出了一种检测技术,可识别器械在超声容积内的位置。该算法使用广义拉东变换的一种形式在超声图像中搜索长直物体,这是器械的一个特征,而在心脏组织中不存在。当与放置在器械轴上的被动标记相结合时,可在三维空间中找到器械的完整位置和方向。这种检测技术适合在当前一代个人计算机图形处理器(GPU)上快速执行。我们在GPU上的实现能在31毫秒内检测到手术器械,足以以超声设备每秒25帧容积的速率进行实时跟踪。水槽实验发现器械方向误差为1.1度,尖端位置误差小于1.8毫米。最后,一项体内研究证明了在跳动的猪心脏内成功进行器械跟踪。