Developing a Massively Parallel Forward Projection Radiography Model for Large-Scale Industrial Applications
Author(s) -
Matthew Bauerle
Publication year - 2014
Language(s) - English
Resource type - Reports
DOI - 10.2172/1171557
Subject(s) - massively parallel , computer science , projection (relational algebra) , computation , computer graphics (images) , voxel , graphics , pixel , computer graphics , scale (ratio) , graphics processing unit , computer vision , cuda , parallel computing , artificial intelligence , computational science , algorithm , cartography , geography
This project utilizes Graphics Processing Units (GPUs) to compute radiograph simulations for arbitrary objects. The generation of radiographs, also known as the forward projection imaging model, is computationally intensive and not widely utilized. The goal of this research is to develop a massively parallel algorithm that can compute forward projections for objects with a trillion voxels (3D pixels). To achieve this end, the data are divided into blocks that can each fit into GPU memory. The forward projected image is also divided into segments to allow for future parallelization and to avoid needless computations.
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