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Interactive Depth of Focus for Improved Depth Perception

机译:交互式焦点深度可改善深度感知

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The need to look into human body for better diagnosis, improved surgical planning and minimally invasive surgery led to breakthroughs in medical imaging. But, intra-operatively a surgeon needs to look at multi-modal imaging data on multiple displays and to fuse the multi-modal data in the context of the patient. This adds extra mental effort for the surgeon in an already high cognitive load surgery. The obvious solution to augment medical object in the context of patient suffers from inaccurate depth perception. In the past, some visualizations have addressed the issue of wrong depth perception, but not without interfering with the natural intuitive view of the surgeon. Therefore, in the current work an interactive depth of focus (DoF) blur method for AR is proposed. It mimics the naturally present DoF blur effect in a microscope. DoF blur forces the cue of accommodation and convergence to come into effect and holds potential to give near metric accuracy; its quality decreases with distance. This makes it suitable for microscopic neurosurgical applications with smaller working depth ranges.
机译:为了更好地诊断,改进手术计划和微创手术,需要深入研究人体,这导致了医学成像方面的突破。但是,术中外科医生需要在多个显示器上查看多模态成像数据,并在患者背景下融合多模态数据。在已经很高的认知负荷手术中,这为外科医生增加了额外的精力。在患者的情况下增加医疗对象的明显解决方案遭受不正确的深度感知。过去,一些可视化解决了错误的深度感知问题,但并非没有干扰外科医生的自然直观视野。因此,在当前工作中,提出了一种用于AR的交互式景深(DoF)模糊方法。它模仿显微镜中自然出现的DoF模糊效果。 DoF模糊迫使调节和收敛的提示生效,并具有提供接近度量精度的潜力。其质量随距离而降低。这使其适用于工作深度范围较小的显微神经外科应用。

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