STTR Phase I: Computerized System for Detection, Assessment, and Visualization of Intraoperative Bleeding During Robotic and Laparoscopic Surgery

这个小型企业技术转让(STTR)第一阶段项目的更广泛的影响/商业潜力是降低接受手术的患者的发病率和死亡率。手术中的不慎出血是一个严重的问题，在世界各地数百万患者的所有类型的手术中都会发生。该项目将推进一个机器人手术工具系统，使用人工智能(AI)来管理术中出血。减少失血将减少对输血的需求，降低医疗费用，并改善手术后的康复。这项技术将为不断发展的手术工具制造商市场推进插接式安全实用程序的通用标准。小企业技术转移(STTR)第一阶段项目将促进智能术中系统的转换。目前，还没有工具来检测或描述出血的特征，所以外科医生必须持续监控摄像机的视野是否有出血，并估计出血的来源，出血通常淹没在血泊中。这项拟议的工作将推进一个原型，以帮助外科医生在泌尿外科手术期间实时检测、可视化和表征动脉出血。出血的来源将使用2D或3D(增强现实)覆盖显示给外科医生，使他/她能够准确和快速地控制出血。这项技术以一种新颖的方式融合了机器人学、计算机视觉和机器学习，以产生一种将显著推进当前最先进水平的手术工具。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to reduce the morbidity and mortality of patients undergoing surgery. Inadvertent bleeding during surgery represents a critical problem that occurs during all types of procedures on millions of patients around the world. This project will advance a robotic surgical tool system using artificial intelligence (AI) to manage intraoperative bleeding. Reduced blood loss will lead to a reduced demand for blood transfusions, reduced healthcare costs, and improved recuperation from surgery. This technology will advance a universal standard for bolt-on safety utilities to the evolving surgical tool manufacturer market.The Small Business Technology Transfer (STTR) Phase I project will advance the translation of an intelligent intraoperative system. Currently, there is no tool to detect or characterize bleeding, so the surgeon must continually monitor the camera view for bleeding and estimate the source of the bleed, which is often submerged in a pool of blood. The proposed effort will advance a prototype to assist a surgeon in detecting, visualizing, and characterizing arterial bleeding in real time during urological surgery. The source of the bleeding will be presented to the surgeon using 2D or 3D (augmented reality) overlays, enabling him/her to control the bleeding precisely and quickly. The technology fuses robotics, computer vision, and machine learning in a novel manner to produce a surgical tool that will significantly advance the current state-of-the-art.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.