研究目的
To present a gesture-based method for manual registration correction in augmented reality (AR) neuronavigation systems to compensate for the effects of brainshift, misregistration, or tracking errors.
研究成果
The gesture-based method for manual registration correction in AR neuronavigation systems is a valuable option, achieving accuracy comparable to previously proposed methods. It is simpler and quicker to use, with minimal impact on the surgical workflow. Future improvements could enhance usability and accuracy.
研究不足
The method's accuracy is limited by the initial misregistration RMS error, with better performance observed for larger shifts (>4 mm). The study also noted technical issues such as jitter, latency, and sensitivity that could impact accuracy.
1:Experimental Design and Method Selection:
The study involved testing a gesture-based method for manual registration correction using a tablet's touchscreen capabilities in a laboratory setting.
2:Sample Selection and Data Sources:
Ten subjects participated in the study, using a 3D printed phantom head for testing.
3:List of Experimental Equipment and Materials:
The system comprised a Polaris Tracking System, an iPad with a developed AR App, the IBIS Neuronav open-source platform, and a wireless router.
4:Experimental Procedures and Operational Workflow:
Subjects were presented with misregistered AR views and asked to correct the registration using touchscreen gestures.
5:Data Analysis Methods:
The outcomes measured were registration RMS error after re-registration, percentage correction from the initial misregistration, total time to re-register, and the number of tablet displacements.
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