Inspiration
Description An integrated platform that leverages ChatGPT to guide users to learn complex physiological movements through visual cues in an AR/VR interface environment.
The workflow entails two components: Anatomical Segmentation Module (Trained ML Model) that outputs segmented DICOMs 3D .STL Generator that inputs segmented DICOMs and outputs 3D .STL models into Microsoft HoloLens
Publications SPIE Augmented Reality Headset Project (2022): https://spie.org/Publications/Proceedings/Paper/10.1117/12.2612993?SSO=1
2022 Penn HealthX Pitch: https://drive.google.com/file/d/1C1gpfMtL6qcC5LbIcg5wG8lb_eN22bXR/view?usp=sharing
Deep Learning Automatic 3D Segmentation of Mandible from Cone Beam CT for Preoperative Planning (2022): https://www.joms.org/article/S0278-2391(22)00606-1/fulltext
2022 Fall Research Fair Presentation: https://presentations.curf.upenn.edu/poster/fully-digitally-integrated-workflow-brain-mri-point-cloud-generation-and-augmented-reality
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