Virtual reality for synergistic surgical training and data generation
Virtual reality for synergistic surgical training and data generation
复制标题
用于协同手术训练和数据生成的虚拟现实
DOI:
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发表时间:
2021
期刊:
影响因子:
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通讯作者:
M. Unberath
中科院分区:
文献类型:
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作者:
A. Munawar;Zhaoshuo Li;Punit Kunjam;N. Nagururu;Andy S Ding;P. Kazanzides;T. Looi;Francis X Creighton;Russell H. Taylor;M. Unberath
ABSTRACT Surgical simulators not only allow planning and training of complex procedures, but also offer the ability to generate structured data for algorithm development, which may be applied in image-guided computer assisted interventions. While there have been efforts on either developing training platforms for surgeons or data generation engines, these two features, to our knowledge, have not been offered together. We present our developments of a cost-effective and synergistic framework, named Asynchronous Multibody Framework Plus (AMBF+), which generates data for downstream algorithm development simultaneously with users practicing their surgical skills. AMBF+ offers stereoscopic display on a virtual reality (VR) device and haptic feedback for immersive surgical simulation. It can also generate diverse data such as object poses and segmentation maps. AMBF+ is designed with a flexible plugin setup that allows for unobtrusive extension for simulation of different surgical procedures. We show one use case of AMBF+ as a virtual drilling simulator for lateral skull-base surgery, where users can actively modify the patient anatomy using a virtual surgical drill. We further demonstrate how the data generated can be used for validating and training downstream computer vision algorithms.
影响因子:
5.2
作者:
Munawar, Adnan;Wu, Jie Ying;Fischer, Gregory S.
通讯作者:
Fischer, Gregory S.