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Proceedings Paper

OpenVCT: a GPU-accelerated virtual clinical trial pipeline for mammography and digital breast tomosynthesis
Author(s): Bruno Barufaldi; David Higginbotham; Predrag R. Bakic; Andrew D. A. Maidment
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Paper Abstract

Virtual clinical trials (VCTs) have a critical role in preclinical testing of imaging systems. A VCT pipeline has been developed to model the human body anatomy, image acquisition systems, display and processing, and image analysis and interpretation. VCTs require the execution of multiple computer simulations in a reasonable time. This study presents the OpenVCT Framework, consisting of graphical software to design a sequence of processing steps for the VCT pipeline; management software that coordinates the pipeline execution, manipulates, and retrieves phantoms and images using a relational database; and a server that executes the individual steps of the virtual patient accrual process using GPU optimized software. The framework is modular and supports various data types, algorithms, and modalities. The framework can be used to conduct massive simulations and several hundred imaging studies can be simulated per day on a single workstation. On average, we can simulate a Tomo Combo (DM + DBT) study using anthropomorphic breast phantoms in less than 9 minutes (voxel size = 100 μm3 and volume = 700 mL). Tomo Combo images from an entire virtual population can be simulated in less than a week. We can accelerate system performance using phantoms with large voxels. The VCT pipeline can also be accelerated by using multiple GPU’s (e.g., using SLI mode, GPU clusters).

Paper Details

Date Published: 9 March 2018
PDF: 8 pages
Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 1057358 (9 March 2018); doi: 10.1117/12.2294935
Show Author Affiliations
Bruno Barufaldi, The Univ. of Pennsylvania (United States)
David Higginbotham, The Univ. of Pennsylvania (United States)
Predrag R. Bakic, The Univ. of Pennsylvania (United States)
Andrew D. A. Maidment, The Univ. of Pennsylvania (United States)


Published in SPIE Proceedings Vol. 10573:
Medical Imaging 2018: Physics of Medical Imaging
Joseph Y. Lo; Taly Gilat Schmidt; Guang-Hong Chen, Editor(s)

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