Accelerating advanced MRI reconstructions on GPUs
Journal of Parallel and Distributed Computing
Real-Time Optical Flow Calculations on FPGA and GPU Architectures: A Comparison Study
FCCM '08 Proceedings of the 2008 16th International Symposium on Field-Programmable Custom Computing Machines
Parallel Backprojector for Cone-Beam Computer Tomography
RECONFIG '08 Proceedings of the 2008 International Conference on Reconfigurable Computing and FPGAs
Accelerating Compute-Intensive Applications with GPUs and FPGAs
SASP '08 Proceedings of the 2008 Symposium on Application Specific Processors
IEEE Micro
State-of-the-art in heterogeneous computing
Scientific Programming
GPU-based cone beam computed tomography
Computer Methods and Programs in Biomedicine
Evaluation of the reconfiguration of the data acquisition system for 3D USCT
International Journal of Reconfigurable Computing - Special issue on selected papers from the international workshop on reconfigurable communication-centric systems on chips (ReCoSoC' 2010)
UWB microwave imaging for breast cancer detection: Many-core, GPU, or FPGA?
ACM Transactions on Embedded Computing Systems (TECS) - Special Issue on Design Challenges for Many-Core Processors, Special Section on ESTIMedia'13 and Regular Papers
Recent progress and challenges in exploiting graphics processors in computational fluid dynamics
The Journal of Supercomputing
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As today's standard screening methods frequently fail to diagnose breast cancer before metastases have developed, earlier breast cancer diagnosis is still a major challenge. Three-dimensional ultrasound computer tomography promises high-quality images of the breast, but is currently limited by a time-consuming image reconstruction. In this work, we investigate the acceleration of the image reconstruction by GPUs and FPGAs. We compare the obtained performance results with a recent multi-core CPU. We show that both architectures are able to accelerate processing, whereas the GPU reaches the highest performance. Furthermore, we draw conclusions in terms of applicability of the accelerated reconstructions in future clinical application and highlight general principles for speed-up on GPUs and FPGAs.