{"id":2440,"date":"2024-05-03T16:39:59","date_gmt":"2024-05-03T16:39:59","guid":{"rendered":"https:\/\/labs.cs.queensu.ca\/perklab\/members\/emily-rae\/"},"modified":"2024-05-03T16:39:59","modified_gmt":"2024-05-03T16:39:59","slug":"emily-rae","status":"publish","type":"qsc_member","link":"https:\/\/labs.cs.queensu.ca\/perklab\/members\/emily-rae\/","title":{"rendered":"Emily Rae"},"content":{"rendered":"
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Emily Rae<\/h1>\n<\/div>\n
Undergraduate Student<\/div>\n
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Queen’s University<\/div>\n
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Emily was an undegraduate research assistant at the Perk Lab, presnently in MSc at the University of Glasgow.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n

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Baum, Zachary M C; Lasso, Andras; Ryan, Sarah; Ungi, Tamas; Rae, Emily; Zevin, Boris; Levy, Ron; Fichtinger, Gabor<\/p>

Augmented reality training platform for neurosurgical burr hole localization<\/a> Journal Article<\/span> <\/p>

In: <\/span>Journal of Medical Robotics Research, <\/span>vol. 4, <\/span>no. 3-4, <\/span>pp. 1942001-1 - 1942001-13, <\/span>2019<\/span>.<\/p>

Abstract<\/a><\/span> | Links<\/a><\/span> | BibTeX<\/a><\/span><\/p>

@article{Baum2020,
\r\ntitle = {Augmented reality training platform for neurosurgical burr hole localization},
\r\nauthor = {Zachary M C Baum and Andras Lasso and Sarah Ryan and Tamas Ungi and Emily Rae and Boris Zevin and Ron Levy and Gabor Fichtinger},
\r\nurl = {https:\/\/labs.cs.queensu.ca\/perklab\/wp-content\/uploads\/sites\/3\/2024\/02\/Baum2020a.pdf},
\r\ndoi = {https:\/\/doi.org\/10.1142\/S2424905X19420017},
\r\nyear  = {2019},
\r\ndate = {2019-01-01},
\r\nurldate = {2019-01-01},
\r\njournal = {Journal of Medical Robotics Research},
\r\nvolume = {4},
\r\nnumber = {3-4},
\r\npages = {1942001-1 - 1942001-13},
\r\nabstract = {<p>Augmented reality (AR) is used in neurosurgery to visualize lesions and plan procedures pre-operatively and intra-operatively, though its use has not been widely adopted in simulation-based neurosurgical training for the same tasks. This work defines metrics to determine performance in drill position and angle identification for neurosurgical training. The metrics were validated intra-operatively and in a simulated training environment, demonstrating that trainees identify drill position and angle faster and more accurately with AR compared to standard techniques. Training using AR and the proposed metrics stands to add value to neurosurgical curricula development.<\/p>},
\r\nkeywords = {},
\r\npubstate = {published},
\r\ntppubtype = {article}
\r\n}
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<p>Augmented reality (AR) is used in neurosurgery to visualize lesions and plan procedures pre-operatively and intra-operatively, though its use has not been widely adopted in simulation-based neurosurgical training for the same tasks. This work defines metrics to determine performance in drill position and angle identification for neurosurgical training. The metrics were validated intra-operatively and in a simulated training environment, demonstrating that trainees identify drill position and angle faster and more accurately with AR compared to standard techniques. Training using AR and the proposed metrics stands to add value to neurosurgical curricula development.<\/p><\/div>
Close<\/a><\/p><\/div>