Needle guidance in soft tissue

图像引导将柔性探针和针放置到可变形目标介质中在制造、组织工程、细胞操作中无处不在，并且可能在医学中具有最大的影响。在加拿大，有数百万人进行针式活检、注射和切除。 在目前的实践中，针经常无法到达预期目标和/或造成过度伤害。 它涉及许多基本的科学挑战，将针引导到嵌入在柔软和可变形介质中的移动目标中，而不造成附带组织损伤。我提出了一种新的计算和成像的组合，使针放置在软组织更安全，更准确。特别是，我将开发新的超声图像计算方法和概率目标位移模型规划的最佳针轨迹。这些方法将在我以前开发的超声引导机器人辅助针放置系统的背景下进行评估。 这项研究的成果将是新的计算方法和软件实现，这些方法和软件实现有可能提高手术针插入程序的准确性，同时也使它们对患者的创伤更小。 该计划将培养两名博士，四名硕士和十名本科生在前沿计算机科学研究与生物医学工程的应用。

Image-guided placement of flexible probes and needles into a deformable target medium is ubiquitous in manufacturing, tissue engineering, cell manipulation, and perhaps with the most impact, in medicine. Needle-based biopsies, injections and implantations are performed by the millions in Canada. In current practice, needles often fail to reach the intended target and/or cause excessive injury. It involves many fundamental scientific challenges to navigate a needle into a moving target embedded in a soft and deformable medium, without causing collateral tissue damage. I propose a novel combination of computing and imaging to make needle placement in soft tissues safer and more accurate. In particular, I will develop novel ultrasound image computing methods and probabilistic target displacement models in planning the optimal needle trajectory. The methods will be evaluated in the context of an ultrasound-guided robot-assisted needle placement system I have developed previously. The outcome of this research will be new computing methods and software implementations that have the potential to increase the accuracy of surgical needle insertion procedures, while also making them less traumatic for the patient. This program will train two PhD, four MSc and ten undergraduate students in leading edge computer science research with applications in biomedical engineering.