GPU-based volume reconstruction for freehand 3D ultrasound imaging

Volume reconstruction plays an important role in improving image quality for freehand three-dimensional (3D) ultrasound imaging. The kernel regression provides an effective method for volume reconstruction in 3D ultrasound imaging, but it requires heavily computational time-cost. In this paper, a pr...

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Bibliographic Details
Main Authors: Tiexiang Wen, Rong Liu, Lei Liu, Wenjian Qin, Ling Li, Jia Gu
Format: Conference Proceeding
Language:English
Subjects:
Graphics processing units
Image reconstruction
Imaging
Instruction sets
Kernel
Three-dimensional displays
Ultrasonic imaging
Online Access:Get full text
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Summary:Volume reconstruction plays an important role in improving image quality for freehand three-dimensional (3D) ultrasound imaging. The kernel regression provides an effective method for volume reconstruction in 3D ultrasound imaging, but it requires heavily computational time-cost. In this paper, a programmable graphic-processor-unit-(GPU) based fast kernel regression method is proposed for freehand 3D ultrasound volume reconstruction. The most significant aspect of our method is the adopting of powerful data-parallel computing capability of GPU to improve the overall efficiency. To produce higher image quality, the results of the kernel regression with various parameter settings is deeply investigated under the help of the fast implementation of the algorithm. Experimental results demonstrate that the computational performance of the proposed GPU-based method can be over 200 times faster than that on CPU. Better image quality for speckle reduction and details preservation can be obtained with the parameter setting of kernel window size of 5×5×5 and kernel bandwidth of 1.0.
ISSN:1557-170X
2694-0604
DOI:10.1109/EMBC.2017.8037661