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使用增强现实耳机的超级分辨率,在手术期间将电极网定位为小的,可变形的物体.

Hizirwan S Salim1, Abdullah Thabit2, Sem Hoogteijling3,4

  • 1High Performance Compute & Visualization, SURF bv, Utrecht, The Netherlands. hizirwan.salim@surf.nl.

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概括
此摘要是机器生成的。

这项研究介绍了一种人工智能增强现实系统,用于精确定位手术网格. 这种新方法的精度低于5毫米,提高了焦点治疗的手术规划.

关键词:
人工智能的人工智能是人工智能.增强现实是一种增强现实.计算机辅助手术是计算机辅助的手术.的手术手术是在的手术.仪器跟踪仪器跟踪仪器跟踪仪器跟踪仪器在外科手术内进行皮质电图.位置估计 位置估计

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科学领域:

  • 神经外科 神经外科
  • 医疗成像医学成像
  • 计算机视觉 计算机视觉

背景情况:

  • 手术为焦点提供了一种潜在的治疗方法.
  • 术内电皮图 (ioECoG) 网格的精确定位对于成功的外科手术结果至关重要.
  • 当前的方法在精确定位小,可变形的ioECoG网格方面面临挑战.

研究的目的:

  • 开发和评估一种用于定位小,可变形物体的新方法,特别是ioECoG网格.
  • 评估使用增强现实 (AR) 头戴显示器 (HMD) 与人工智能 (AI) 集成的可行性.
  • 在手术期间提高ioECoG网格定位的准确性.

主要方法:

  • 开发了一种使用HoloLens 2 AR HMD的图像处理方法.
  • 结合物体检测,超分辨率和姿势估计的人工智能模型与立体三角化.
  • 在9万张图像的合成数据集上训练AI模型.
  • 在受控环境中对光学追踪器进行了系统测试,评估距离在40至90厘米的精度.

主要成果:

  • 在距离小于60厘米的情况下,在定位ioECoG网格时达到5毫米以下的精度.
  • 在40厘米处证明精度低于2毫米,标准偏差小于0.5毫米.
  • 该系统平均每秒处理24个立体声,60厘米.

结论:

  • 该研究证实了使用AR HMD用于定位像ioECoG网格这样的小,可变形物体的可行性.
  • 取得的准确性在临床上是相关的,尽管需要在临床环境中进一步验证.
  • 未来的研究应该专注于评估该方法对手术精度和患者结果的影响.