首页|New Robotics Research from U.S. Army Institute of Surgical Research Described (D esign and testing of ultrasound probe adapters for a robotic imaging platform)

New Robotics Research from U.S. Army Institute of Surgical Research Described (D esign and testing of ultrasound probe adapters for a robotic imaging platform)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on robotics is the subjec t of a new report. According to news originating from the U.S. Army Institute of Surgical Research by NewsRx correspondents, research stated, “Medical imaging-b ased triage is a critical tool for emergency medicine in both civilian and milit ary settings.” Funders for this research include U.S. Department of Defense; Oak Ridge Associat ed Universities. The news editors obtained a quote from the research from U.S. Army Institute of Surgical Research: “Ultrasound imaging can be used to rapidly identify free flui d in abdominal and thoracic cavities which could necessitate immediate surgical intervention. However, proper ultrasound image capture requires a skilled ultras onography technician who is likely unavailable at the point of injury where reso urces are limited. Instead, robotics and computer vision technology can simplify image acquisition. As a first step towards this larger goal, here, we focus on the development of prototypes for ultrasound probe securement using a robotics p latform. The ability of four probe adapter technologies to precisely capture ima ges at anatomical locations, repeatedly, and with different ultrasound transduce r types were evaluated across more than five scoring criteria. Testing demonstra ted two of the adapters outperformed the traditional robot gripper and manual im age capture, with a compact, rotating design compatible with wireless imaging te chnology being most suitable for use at the point of injury.”

U.S. Army Institute of Surgical ResearchEmerging TechnologiesMachine LearningRoboticsRobotsTechnology

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Mar.14)