Toronto Metropolitan University
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Vis3D+ A tightly integrated GPU-accelerated computation and rendering framework for interactive 3D image visualization

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posted on 2021-05-24, 18:33 authored by Irfa Nisar
This thesis presents extensions to an interactive 3D image visualization framework. The existing software framework provides functionality for interactively visualizing 3D medical data. The extensions consist of software modules that execute directly on the graphics hardware, utilizing the massively parallel, general-purpose computing platform provided by modern graphics processing units (GPUs). These GPUbased software modules are designed to support the execution of volume image processing algorithms, implemented using recently available GPU programs known as “compute shaders”, as well as to support interactive editing of the algorithms’ output. The new modules are seamlessly integrated as new stages in a GPU-based rendering pipeline provided by the existing framework. In this thesis, an example volume image processing algorithm known as level set segmentation is implemented and demonstrated. In addition, a new editing module is demonstrated that enables user modification of this algorithm’s output by extending a pre-existing volume “painting” interface.



  • Master of Science


  • Computer Science

Granting Institution

Ryerson University

LAC Thesis Type

  • Thesis