Literature DB >> 26773787

Sparse deconvolution method for ultrasound images based on automatic estimation of reference signals.

Haoran Jin1, Keji Yang1, Shiwei Wu1, Haiteng Wu1, Jian Chen2.   

Abstract

Sparse deconvolution is widely used in the field of non-destructive testing (NDT) for improving the temporal resolution. Generally, the reference signals involved in sparse deconvolution are measured from the reflection echoes of standard plane block, which cannot accurately describe the acoustic properties at different spatial positions. Therefore, the performance of sparse deconvolution will deteriorate, due to the deviations in reference signals. Meanwhile, it is inconvenient for automatic ultrasonic NDT using manual measurement of reference signals. To overcome these disadvantages, a modified sparse deconvolution based on automatic estimation of reference signals is proposed in this paper. By estimating the reference signals, the deviations would be alleviated and the accuracy of sparse deconvolution is therefore improved. Based on the automatic estimation of reference signals, regional sparse deconvolution is achievable by decomposing the whole B-scan image into small regions of interest (ROI), and the image dimensionality is significantly reduced. Since the computation time of proposed method has a power dependence on the signal length, the computation efficiency is therefore improved significantly with this strategy. The performance of proposed method is demonstrated using immersion measurement of scattering targets and steel block with side-drilled holes. The results verify that the proposed method is able to maintain the vertical resolution enhancement and noise-suppression capabilities in different scenarios.
Copyright © 2016 Elsevier B.V. All rights reserved.

Keywords:  Reference signal; SpaRSA algorithm; Sparse deconvolution; Ultrasonic B-scan image; Vertical resolution

Year:  2015        PMID: 26773787     DOI: 10.1016/j.ultras.2015.12.011

Source DB:  PubMed          Journal:  Ultrasonics        ISSN: 0041-624X            Impact factor:   2.890


  2 in total

1.  Sparse Reconstruction for Micro Defect Detection in Acoustic Micro Imaging.

Authors:  Yichun Zhang; Tielin Shi; Lei Su; Xiao Wang; Yuan Hong; Kepeng Chen; Guanglan Liao
Journal:  Sensors (Basel)       Date:  2016-10-24       Impact factor: 3.576

2.  Video-rate all-optical ultrasound imaging.

Authors:  Erwin J Alles; Sacha Noimark; Efthymios Maneas; Edward Z Zhang; Ivan P Parkin; Paul C Beard; Adrien E Desjardins
Journal:  Biomed Opt Express       Date:  2018-07-02       Impact factor: 3.732

  2 in total

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