Paper
29 March 2013 GPU based acceleration of 3D USCT image reconstruction with efficient integration into MATLAB
Ernst Kretzek, Michael Zapf, Matthias Birk, Hartmut Gemmeke, Nicole V. Ruiter
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Abstract
3D ultrasound computer tomography (3D USCT) promises reproducible high-resolution images for early detection of breast tumors. The synthetic aperture focusing technique (SAFT) used for image reconstruction is highly computeintensive but suitable for an accelerated execution on GPUs. In this paper we investigate how a previous implementation of the SAFT algorithm in CUDA C can be further accelerated and integrated into the existing MATLAB signal and image processing chain for 3D USCT. The focus is on an efficient preprocessing and preparation of data blocks in MATLAB as well as an improved utilisation of special hardware like the texture fetching units on GPUs. For 64 slices with 1024×1024 pixels each the overall runtime of the reconstruction including data loading and preprocessing could be decreased from 35 hours with CPU to 2.4 hours with eight GPUs.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ernst Kretzek, Michael Zapf, Matthias Birk, Hartmut Gemmeke, and Nicole V. Ruiter "GPU based acceleration of 3D USCT image reconstruction with efficient integration into MATLAB", Proc. SPIE 8675, Medical Imaging 2013: Ultrasonic Imaging, Tomography, and Therapy, 86750O (29 March 2013); https://doi.org/10.1117/12.2007184
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Cited by 10 scholarly publications.
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KEYWORDS
MATLAB

3D image processing

Image restoration

Reconstruction algorithms

Signal processing

3D image reconstruction

Image processing

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