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  • 标题:From AR to AI: Augmentation Technology for Intelligent Surgery and Medical Treatments
  • 本地全文:下载
  • 作者:Mei Zhang ; Zhicheng Zhang ; Xiao Wang
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:5
  • 页码:792-796
  • DOI:10.1016/j.ifacol.2021.04.174
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractWith the development of augmented reality (AR) technologies, more and more approaches are proposed for medical applications. With the help of AR technology, the doctor can highly improve the spatial perception and obtain more information beneath the displayed image. Generally, 3D reconstruction, registration, tracking and depth visualization are all important for an AR system, which directly determine the accuracy of the system. However, none of recent systems have achieved a perfect 3D vision for doctors. It is particularly challenging for the AR system to perform well for operation on highly deformable body tissues. Therefore, there is an urgent need to improve the 3D vision and intelligence of AR systems. In this paper, we provide a review of the recent development of augmentation technologies for surgery and medical treatment. And then, we introduce the parallel intelligence theory into AR systems, which can provide a feasible approach to enhance the efficiency.
  • 关键词:KeywordsPotential impact of automationopen problemsAugmented realityMedical treatmentParallel theory3D technology
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