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首页> 外文会议>Augmented reality environments for medical imaging and computer-assisted interventions >Uncertainty-Encoded Augmented Reality for Robot-Assisted Partial Nephrectomy: A Phantom Study
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Uncertainty-Encoded Augmented Reality for Robot-Assisted Partial Nephrectomy: A Phantom Study

机译：机器人辅助部分肾切除术的不确定性编码增强现实：幻像研究

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摘要

In most robot-assisted surgical interventions, multimodal fusion of pre- and intra-operative data is highly valuable, affording the surgeon a more comprehensive understanding of the surgical scene observed through the stereo endoscopic camera. More specifically, in the case of partial nephrectomy, fusing pre-operative segmentations of kidney and tumor with the stereo endoscopic view can guide tumor localization and the identification of resection margins. However, the surgeons are often unable to reliably assess the levels of trust they can bestow on what is overlaid on the screen. In this paper, we present the proof-of-concept of an uncertainty-encoded augmented reality framework and novel visualizations of the uncertainties derived from the pre-operative CT segmentation onto the surgeon's stereo endoscopic view. To verify its clinical potential, the proposed method is applied to an ex vivo lamb kidney. The results are contrasted to different visualization solutions based on crisp segmentation demonstrating that our method provides valuable additional information that can help the surgeon during the resection planning.
机译：在大多数机器人辅助的外科手术中，术前和术中数据的多模式融合非常有价值，从而使外科医生对通过立体内窥镜摄像机观察到的手术场景有更全面的了解。更具体地说，在部分肾切除术的情况下，将术前肾脏和肿瘤的切开与立体内窥镜融合在一起，可以指导肿瘤的定位和切除切缘的识别。但是，外科医生通常无法可靠地评估他们可以对屏幕上覆盖的内容给予的信任级别。在本文中，我们介绍了不确定性编码的增强现实框架的概念证明，以及从术前CT分割到外科医生的立体内窥镜视图上得出的不确定性的新颖可视化。为了验证其临床潜力，将所提出的方法应用于离体羔羊肾脏。结果与基于清晰分割的不同可视化解决方案形成对比，表明我们的方法提供了有价值的附加信息，可在手术切除计划中帮助外科医生。

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