Artificial intelligence- and computer-assisted navigation for shoulder surgery.

IF 1.6 4区 医学
Kang-San Lee, Seung Ho Jung, Dong-Hyun Kim, Seok Won Chung, Jong Pil Yoon
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引用次数: 0

Abstract

Background: Over the last few decades, shoulder surgery has undergone rapid advancements, with ongoing exploration and the development of innovative technological approaches. In the coming years, technologies such as robot-assisted surgeries, virtual reality, artificial intelligence, patient-specific instrumentation, and different innovative perioperative and preoperative planning tools will continue to fuel a revolution in the medical field, thereby pushing it toward new frontiers and unprecedented advancements. In relation to this, shoulder surgery will experience significant breakthroughs. Main body: Recent advancements and technological innovations in the field were comprehensively analyzed. We aimed to provide a detailed overview of the current landscape, emphasizing the roles of technologies. Computer-assisted surgery utilizing robotic- or image-guided technologies is widely adopted in various orthopedic specialties. The most advanced components of computer-assisted surgery are navigation and robotic systems, with functions and applications that are continuously expanding. Surgical navigation requires a visual system that presents real-time positional data on surgical instruments or implants in relation to the target bone, displayed on a computer monitor. There are three primary categories of surgical planning that utilize navigation systems. The initial category involves volumetric images, such as ultrasound echogram, computed tomography, and magnetic resonance images. The second type is based on intraoperative fluoroscopic images, and the third type incorporates kinetic information about joints or morphometric data about the target bones acquired intraoperatively. Conclusion: The rapid integration of artificial intelligence and deep learning into the medical domain has a significant and transformative influence. Numerous studies utilizing deep learning-based diagnostics in orthopedics have remarkable achievements and performance.

人工智能和计算机辅助肩部手术导航。
背景:在过去的几十年里,肩部手术经历了快速发展,不断探索和开发创新技术方法。未来几年,机器人辅助手术、虚拟现实、人工智能、患者专用器械以及各种创新的围手术期和术前规划工具等技术将继续推动医疗领域的革命,从而将其推向新的前沿和前所未有的进步。与此相关,肩部手术也将取得重大突破。主体:全面分析了该领域的最新进展和技术创新。我们的目标是详细概述当前的形势,强调技术的作用。利用机器人或图像引导技术的计算机辅助手术在骨科各专科得到广泛采用。计算机辅助手术最先进的组成部分是导航和机器人系统,其功能和应用范围正在不断扩大。手术导航需要一个可视系统,在计算机显示器上显示手术器械或植入物与目标骨骼的实时位置数据。利用导航系统进行手术规划主要有三类。第一类涉及体积图像,如超声回声图、计算机断层扫描和磁共振图像。第二类是基于术中透视图像,第三类是结合术中获得的关节动力学信息或目标骨骼的形态测量数据。结论人工智能和深度学习迅速融入医疗领域,产生了重大的变革性影响。在骨科领域利用基于深度学习的诊断技术进行的大量研究取得了显著的成就和表现。
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来源期刊
自引率
0.00%
发文量
91
期刊介绍: Journal of Orthopaedic Surgery is an open access peer-reviewed journal publishing original reviews and research articles on all aspects of orthopaedic surgery. It is the official journal of the Asia Pacific Orthopaedic Association. The journal welcomes and will publish materials of a diverse nature, from basic science research to clinical trials and surgical techniques. The journal encourages contributions from all parts of the world, but special emphasis is given to research of particular relevance to the Asia Pacific region.
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