Sparse-View Ultrasound Diffraction Tomography Using Compressed Sensing with Nonuniform FFT

Sparse-View Ultrasound Diffraction Tomography Using Compressed Sensing with Nonuniform FFT

Accurate reconstruction of the object from sparse-view sampling data is an appealing issue for ultrasound diffraction tomography (UDT). In this paper, we present a reconstruction method based on compressed sensing framework for sparse-view UDT. Due to the piecewise uniform characteristics of anatomy...

Full description

Bibliographic Details
Main Authors: Hua, Shaoyan, Ding, Mingyue, Yuchi, Ming
Format: Online
Language:English
Published: Hindawi Publishing Corporation 2014
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4020553/
id pubmed-4020553
recordtype oai_dc
spelling pubmed-40205532014-05-27 Sparse-View Ultrasound Diffraction Tomography Using Compressed Sensing with Nonuniform FFT Hua, Shaoyan Ding, Mingyue Yuchi, Ming Research Article Accurate reconstruction of the object from sparse-view sampling data is an appealing issue for ultrasound diffraction tomography (UDT). In this paper, we present a reconstruction method based on compressed sensing framework for sparse-view UDT. Due to the piecewise uniform characteristics of anatomy structures, the total variation is introduced into the cost function to find a more faithful sparse representation of the object. The inverse problem of UDT is iteratively resolved by conjugate gradient with nonuniform fast Fourier transform. Simulation results show the effectiveness of the proposed method that the main characteristics of the object can be properly presented with only 16 views. Compared to interpolation and multiband method, the proposed method can provide higher resolution and lower artifacts with the same view number. The robustness to noise and the computation complexity are also discussed. Hindawi Publishing Corporation 2014 2014-04-24 /pmc/articles/PMC4020553/ /pubmed/24868241 http://dx.doi.org/10.1155/2014/329350 Text en Copyright © 2014 Shaoyan Hua et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Hua, Shaoyan
Ding, Mingyue
Yuchi, Ming
spellingShingle Hua, Shaoyan
Ding, Mingyue
Yuchi, Ming
Sparse-View Ultrasound Diffraction Tomography Using Compressed Sensing with Nonuniform FFT
author_facet Hua, Shaoyan
Ding, Mingyue
Yuchi, Ming
author_sort Hua, Shaoyan
title Sparse-View Ultrasound Diffraction Tomography Using Compressed Sensing with Nonuniform FFT
title_short Sparse-View Ultrasound Diffraction Tomography Using Compressed Sensing with Nonuniform FFT
title_full Sparse-View Ultrasound Diffraction Tomography Using Compressed Sensing with Nonuniform FFT
title_fullStr Sparse-View Ultrasound Diffraction Tomography Using Compressed Sensing with Nonuniform FFT
title_full_unstemmed Sparse-View Ultrasound Diffraction Tomography Using Compressed Sensing with Nonuniform FFT
title_sort sparse-view ultrasound diffraction tomography using compressed sensing with nonuniform fft
description Accurate reconstruction of the object from sparse-view sampling data is an appealing issue for ultrasound diffraction tomography (UDT). In this paper, we present a reconstruction method based on compressed sensing framework for sparse-view UDT. Due to the piecewise uniform characteristics of anatomy structures, the total variation is introduced into the cost function to find a more faithful sparse representation of the object. The inverse problem of UDT is iteratively resolved by conjugate gradient with nonuniform fast Fourier transform. Simulation results show the effectiveness of the proposed method that the main characteristics of the object can be properly presented with only 16 views. Compared to interpolation and multiband method, the proposed method can provide higher resolution and lower artifacts with the same view number. The robustness to noise and the computation complexity are also discussed.
publisher Hindawi Publishing Corporation
publishDate 2014
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4020553/
_version_ 1612088812469485568

Similar Items