Birk M., Guth A., Zapf M., Balzer M., Ruiter N., Hubner M., Becker J.
in Conference on Design and Architectures for Signal and Image Processing, DASIP (2011) 67-74, 6136856. DOI:10.1109/DASIP.2011.6136856
Abstract
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 synthetic aperture focusing technique based image reconstruction. In this work, we investigate the acceleration of the image reconstruction by a GPU, and by the FPGAs embedded in our custom data acquisition system. We compare the obtained performance results with a recent multi-core CPU and show that both platforms are able to accelerate processing. 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. © 2011 IEEE.
Romero-Laorden D.et al.: Analysis of Parallel Computing Strategies to Accelerate Ultrasound Imaging Processes in IEEE Transactions on Parallel and Distributed Systems, 27 (2016) 3429-3440 7437495.
Niemeyer K.et al.: Recent progress and challenges in exploiting graphics processors in computational fluid dynamics in Journal of Supercomputing, 67 (2014) 528-564.
Niemeyer K.et al.: Accelerating reactive-flow simulations using graphics processing units in 51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition 2013 (2013).
Adeshina A.et al.: Multimodal 3-D reconstruction of human anatomical structures using surlens visualization system in Interdisciplinary Sciences: Computational Life Sciences, 5 (2013) 23-36.