TITLE:
Cheetah: A Library for Parallel Ultrasound Beamforming in Multi-Core Systems
AUTHORS:
David Romero-Laorden, Carlos Julián Martín-Arguedas, Javier Villazón-Terrazas, Oscar Martinez-Graullera, Matilde Santos Peñas, César Gutierrez-Fernandez, Ana Jiménez Martín
KEYWORDS:
GPGPU, Ultrasound Image, Beamforming, Array Transducer
JOURNAL NAME:
Journal of Applied Mathematics and Physics,
Vol.3 No.8,
August
26,
2015
ABSTRACT: Developing new imaging methods needs to establish
some proofs of concept before implementing them on real-time scenarios.
Nowadays, the high computational power reached by multi-core CPUs and GPUs have
driven the development of software-based beamformers. Taking this into account,
a library for the fast generation of ultrasound images is presented. It is
based on Synthetic Aperture Imaging Techniques (SAFT) and it is fast because of
the use of parallel computing techniques. Any kind of transducers as well as
SAFT techniques can be defined although it includes some pre-built SAFT methods
like 2R-SAFT and TFM. Furthermore, 2D and 3D imaging (slice- based or full
volume computation) is supported along with the ability to generate both
rectangular and angular images. For interpolation, linear and polynomial
schemes can be chosen. The versatility of the library is ensured by interfacing
it to Matlab, Python and any programming language over different operating
systems. On a standard PC equipped with a single NVIDIA Quadro 4000 (256
cores), the library is able to calculate 262,144 pixels in ≈105 ms using a
linear transducer with 64 elements, and 2,097,152 voxels in ≈ 5 seconds using a
matrix transducer with 121 elements when TFM is applied.