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|a 10.1109/TVCG.2023.3260001
|2 doi
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|a eng
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| 100 |
1 |
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|a Li, Ruiyang
|e verfasserin
|4 aut
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| 245 |
1 |
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|a A Comparative Evaluation of Optical See-Through Augmented Reality in Surgical Guidance
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|c 2024
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|a Text
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|a Date Completed 27.06.2024
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|a Date Revised 28.06.2024
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a During traditional surgeries, planning and instrument guidance is displayed on an external screen. Recent developments of augmented reality (AR) techniques can overcome obstacles including hand-eye discoordination and heavy mental load. Among these AR technologies, optical see-through (OST) schemes with stereoscopic displays can provide depth perception and retain the physical scene for safety considerations. However, limitations still exist in certain AR systems and the influence of these factors on surgical performance is yet to explore. To this end, experiments of multi-scale surgical tasks were carried out to compare head-mounted display (HMD) AR and autostereoscopic image overlay (AIO) AR, concerning objective performance and subjective evaluation. To solely analyze effects brought by display techniques, the tracking system in each included display system was identical and similar tracking accuracy was proved by a preliminary experiment. Focus and context rendering was utilized to enhance in-situ visualization for surgical guidance. Latency values of all display systems were assessed and a delay experiment proved the latency differences had no significant impact on user performance. Results of multi-scale surgical tasks showed that HMD outperformed in detailed operations probably due to stable resolution along the depth axis, while AIO had better performance in larger-scale operations for better depth perception. This article helps point out the critical limitations of current OST AR techniques and potentially promotes the progress of AR applications in surgical guidance
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|a Journal Article
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| 650 |
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|a Comparative Study
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| 700 |
1 |
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|a Han, Boxuan
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Li, Haowei
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Ma, Longfei
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Zhang, Xinran
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Zhao, Zhe
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Liao, Hongen
|e verfasserin
|4 aut
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| 773 |
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|t IEEE transactions on visualization and computer graphics
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|g 30(2024), 7 vom: 07. Juni, Seite 4362-4374
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|g volume:30
|g year:2024
|g number:7
|g day:07
|g month:06
|g pages:4362-4374
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|u http://dx.doi.org/10.1109/TVCG.2023.3260001
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