Presentation
10 April 2023 A fully digitally integrated workflow for brain MRI Point Cloud generation and augmented reality 3D model visualization
Author Affiliations +
Abstract
This study aims to refine an automated workflow for neuroimages that generates three-dimensional (3D) point clouds in the Polygon File Format (.ply) to be deployed into augmented reality (AR) head mount displays (HMD). Our current work involves enhancing and refining core features, along with improving the point-cloud application to optimize the brain MRI intake. Our brain image segmentation algorithm and web-based point cloud generator show promise for clinical workflows, where high-quality point-cloud AR models can be generated from patient MRIs.
Conference Presentation
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jerry Y. Cai, Min-Keun (Kevin) Song, Gabriel Soliman, Raveen Kariyawasam, Pranav Kodali, Albert Chen, Albi Domi, Laura Cai, Josiah Somani, and Chamith Rajapakse "A fully digitally integrated workflow for brain MRI Point Cloud generation and augmented reality 3D model visualization", Proc. SPIE 12469, Medical Imaging 2023: Imaging Informatics for Healthcare, Research, and Applications, 124690I (10 April 2023); https://doi.org/10.1117/12.2654414
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KEYWORDS
3D modeling

Augmented reality

Magnetic resonance imaging

Brain

Clouds

Autoregressive models

Process modeling

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