Accelerated Nonlinear Multichannel Ultrasonic Tomographic Imaging Using Target Sparseness

This paper presents an accelerated iterative Landweber method for nonlinear ultrasonic tomographic imaging in a multiple-input multiple-output (MIMO) configuration under a sparsity constraint on the image. The proposed method introduces the emerging MIMO signal processing techniques and target spars...

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Bibliographic Details
Published in:IEEE transactions on image processing 2014-03, Vol.23 (3), p.1379-1393
Main Authors: Dong, Chengdong, Jin, Yuanwei, Lu, Enyue
Format: Article
Language:English
Subjects:
accelerated projected steepest descent method
Acoustics
Algorithms
Applied sciences
Convergence
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
Image reconstruction
Imaging
Information, signal and communications theory
Inverse problems
Iterative methods
Mathematical models
MIMO
multiple-input multiple-output
Nonlinear Dynamics
Nonlinearity
Reproducibility of Results
Sensitivity and Specificity
Signal and communications theory
Signal processing
Signal, noise
sparsity constraints
Telecommunications and information theory
Tomography
Transaction processing
Ultrasonic testing
Ultrasonic tomography
Ultrasonography - methods
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Summary:This paper presents an accelerated iterative Landweber method for nonlinear ultrasonic tomographic imaging in a multiple-input multiple-output (MIMO) configuration under a sparsity constraint on the image. The proposed method introduces the emerging MIMO signal processing techniques and target sparseness constraints in the traditional computational imaging field, thus significantly improves the speed of image reconstruction compared with the conventional imaging method while producing high quality images. Using numerical examples, we demonstrate that incorporating prior knowledge about the imaging field such as target sparseness accelerates significantly the convergence of the iterative imaging method, which provides considerable benefits to real-time tomographic imaging applications.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2014.2302679