An Assessment of Iterative Reconstruction Methods for Sparse Ultrasound Imaging
Graduate Program in Electrical and Computer Engineering (CPGEI), Federal University of Technology, Paraná (UTFPR), Curitiba PR 80230-901, Brazil
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 9 January 2017 / Revised: 21 February 2017 / Accepted: 28 February 2017 / Published: 8 March 2017
Ultrasonic image reconstruction using inverse problems has recently appeared as an alternative to enhance ultrasound imaging over beamforming methods. This approach depends on the accuracy of the acquisition model used to represent transducers, reflectivity, and medium physics. Iterative methods, well known in general sparse signal reconstruction, are also suited for imaging. In this paper, a discrete acquisition model is assessed by solving a linear system of equations by an
-regularized least-squares minimization, where the solution sparsity may be adjusted as desired. The paper surveys 11 variants of four well-known algorithms for sparse reconstruction, and assesses their optimization parameters with the goal of finding the best approach for iterative ultrasound imaging. The strategy for the model evaluation consists of using two distinct datasets. We first generate data from a synthetic phantom that mimics real targets inside a professional ultrasound phantom device. This dataset is contaminated with Gaussian noise with an estimated SNR, and all methods are assessed by their resulting images and performances. The model and methods are then assessed with real data collected by a research ultrasound platform when scanning the same phantom device, and results are compared with beamforming. A distinct real dataset is finally used to further validate the proposed modeling. Although high computational effort is required by iterative methods, results show that the discrete model may lead to images closer to ground-truth than traditional beamforming. However, computing capabilities of current platforms need to evolve before frame rates currently delivered by ultrasound equipments are achievable.
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Valente, S.A.; Zibetti, M.V.W.; Pipa, D.R.; Maia, J.M.; Schneider, F.K. An Assessment of Iterative Reconstruction Methods for Sparse Ultrasound Imaging. Sensors 2017, 17, 533.
Valente SA, Zibetti MVW, Pipa DR, Maia JM, Schneider FK. An Assessment of Iterative Reconstruction Methods for Sparse Ultrasound Imaging. Sensors. 2017; 17(3):533.
Valente, Solivan A.; Zibetti, Marcelo V.W.; Pipa, Daniel R.; Maia, Joaquim M.; Schneider, Fabio K. 2017. "An Assessment of Iterative Reconstruction Methods for Sparse Ultrasound Imaging." Sensors 17, no. 3: 533.
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