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Sparse-view ultrasound diffraction tomography using compressed sensing with nonuniform FFT.

Hua S, Ding M, Yuchi M - Comput Math Methods Med (2014)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Image Processing and Intelligence Control Key Laboratory of Education Ministry of China, Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.

ABSTRACT
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.

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(a) Original image. (b) Image reconstructed using interpolation method. (c) Image reconstructed using broadband signal. (d) Image reconstructed using CS.
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fig4: (a) Original image. (b) Image reconstructed using interpolation method. (c) Image reconstructed using broadband signal. (d) Image reconstructed using CS.

Mentions: In order to evaluate the performance of the proposed method for UDT reconstruction, we have performed a series of numerical experiments for the phantom in Figure 4(a). The phantom consists of ten ellipses which looks like the well-known Shepp-Logan “head phantom” for CT imaging. However, for UDT system, we have modified the gray levels to those used by [8, 9]. The gray levels represent the relative change in refractive index from the background value of 1.0; the maximum and minimum gray intensity are set to 1.0 and 0, respectively. The speed of sound of the background media is 1500 m/s. To evaluate our method, the scattered field was calculated based on FDT under Born approximation. Although the Born approximation imposes limitation on the dimension of the object for real application [4] and cannot distinguish the features of the object spaced less than λ/2 [52, 53], it can provide a simple and direct method to reconstruct the structure of an object from the measurement of the scattered field. According to FDT, the Fourier transform of the scattered field measured on η = l is proportional to Fourier transform of the object over an arc (2), while the Fourier transform of each ellipse has simple analytical expression; hence we can generate the scattered data through inverse Fourier transform. This procedure not only is fast but also allows the scattered date to be calculated for testing the reconstruction algorithms and experiments parameters such as pitch and number of elements [4, 8–10].


Sparse-view ultrasound diffraction tomography using compressed sensing with nonuniform FFT.

Hua S, Ding M, Yuchi M - Comput Math Methods Med (2014)

(a) Original image. (b) Image reconstructed using interpolation method. (c) Image reconstructed using broadband signal. (d) Image reconstructed using CS.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4020553&req=5

fig4: (a) Original image. (b) Image reconstructed using interpolation method. (c) Image reconstructed using broadband signal. (d) Image reconstructed using CS.
Mentions: In order to evaluate the performance of the proposed method for UDT reconstruction, we have performed a series of numerical experiments for the phantom in Figure 4(a). The phantom consists of ten ellipses which looks like the well-known Shepp-Logan “head phantom” for CT imaging. However, for UDT system, we have modified the gray levels to those used by [8, 9]. The gray levels represent the relative change in refractive index from the background value of 1.0; the maximum and minimum gray intensity are set to 1.0 and 0, respectively. The speed of sound of the background media is 1500 m/s. To evaluate our method, the scattered field was calculated based on FDT under Born approximation. Although the Born approximation imposes limitation on the dimension of the object for real application [4] and cannot distinguish the features of the object spaced less than λ/2 [52, 53], it can provide a simple and direct method to reconstruct the structure of an object from the measurement of the scattered field. According to FDT, the Fourier transform of the scattered field measured on η = l is proportional to Fourier transform of the object over an arc (2), while the Fourier transform of each ellipse has simple analytical expression; hence we can generate the scattered data through inverse Fourier transform. This procedure not only is fast but also allows the scattered date to be calculated for testing the reconstruction algorithms and experiments parameters such as pitch and number of elements [4, 8–10].

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Image Processing and Intelligence Control Key Laboratory of Education Ministry of China, Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.

ABSTRACT
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.

Show MeSH