Published August 2019
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OVS+Tumor: a tool for enhanced lung tumor annotation in VR for machine learning training and analysis
Chicago
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Abstract
OVS+Tumor creates a seamless VR environment designed for intuitive interaction aiding in the complex task of parsing through 3D CT-scans and annotating candidate tumors. Through interactive subsetting and on-the-fly iso-cloud generation, a wider range of users beyond just domain experts (radiologists/surgeons) can generate a viable machine-learning training dataset.
Additional Information
© 2019. Copyright is held by the owner/author(s). We would like to thank the guidance and aid from Jim Barry, Mathieu Desbrun, and Matt Thomson; as well as acknowledge funding from the Interagency Agreement between National Institutes of Health (NIH)/National Cancer Institute (NCI) and NASA, the Chan-Zuckerberg Institute, and Caltech's Student Affairs, and hardware donations from HTC/Vive, Microsoft, NVIDIA, and Logitech which made of this work possible. OVS+Tumor was developed using free/personal versions of Unity, alongside SteamVR, as well as Zen Fulcrum's VR Browser for Unity. Voicework by Ashwini Nayak.Attached Files
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Additional details
- Eprint ID
- 99091
- DOI
- 10.1145/3306449.3328825
- Resolver ID
- CaltechAUTHORS:20191004-134753975
- NASA
- 80NM0018F0855
- NIH
- Chan-Zuckerberg Institute
- Caltech
- Created
-
2019-10-04Created from EPrint's datestamp field
- Updated
-
2021-11-16Created from EPrint's last_modified field
- Caltech groups
- Astronomy Department