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本文引用的文献

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IEEE Trans Comput Imaging. 2023;9:367-382. doi: 10.1109/tci.2023.3261507. Epub 2023 Mar 28.
2
Noninvasive estimation of local speed of sound by pulse-echo ultrasound in a rat model of nonalcoholic fatty liver.应用脉冲回波超声技术无创估计非酒精性脂肪肝大鼠模型局部声速。
Phys Med Biol. 2022 Jan 17;67(1). doi: 10.1088/1361-6560/ac4562.
3
Local Sound Speed Estimation for Pulse-Echo Ultrasound in Layered Media.分层介质中脉冲回波超声的局部声速估计。
IEEE Trans Ultrason Ferroelectr Freq Control. 2022 Feb;69(2):500-511. doi: 10.1109/TUFFC.2021.3124479. Epub 2022 Jan 27.
4
Speed-of-sound imaging using diverging waves.利用发散波进行声速成象。
Int J Comput Assist Radiol Surg. 2021 Jul;16(7):1201-1211. doi: 10.1007/s11548-021-02426-w. Epub 2021 Jun 23.
5
Bayesian Approach for a Robust Speed-of-Sound Reconstruction Using Pulse-Echo Ultrasound.贝叶斯方法在脉冲回波超声中的稳健声速重建中的应用。
IEEE Trans Med Imaging. 2021 Feb;40(2):457-467. doi: 10.1109/TMI.2020.3029286. Epub 2021 Feb 2.
6
Full-waveform inversion imaging of the human brain.人类大脑的全波形反演成像。
NPJ Digit Med. 2020 Mar 6;3:28. doi: 10.1038/s41746-020-0240-8. eCollection 2020.
7
Speed of sound ultrasound transmission tomography image reconstruction based on Bézier curves.基于 Bezier 曲线的超声透射断层成像声速重建。
Ultrasonics. 2020 Apr;103:106097. doi: 10.1016/j.ultras.2020.106097. Epub 2020 Feb 3.
8
A machine learning approach to radiogenomics of breast cancer: a study of 922 subjects and 529 DCE-MRI features.机器学习在乳腺癌放射组学中的应用:一项包含 922 名患者和 529 项 DCE-MRI 特征的研究。
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Contrast Enhancement on Cone-Beam Breast-CT for Discrimination of Breast Cancer Immunohistochemical Subtypes.锥束乳腺CT上的对比增强用于鉴别乳腺癌免疫组织化学亚型
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10
3-D Nonlinear Acoustic Inverse Scattering: Algorithm and Quantitative Results.三维非线性声学逆散射:算法与定量结果。
IEEE Trans Ultrason Ferroelectr Freq Control. 2017 Aug;64(8):1161-1174. doi: 10.1109/TUFFC.2017.2706189. Epub 2017 May 23.

基于块LU求解器的环形阵列超声层析成像中声速和声学衰减的二维逐切片波形反演

2-D Slicewise Waveform Inversion of Sound Speed and Acoustic Attenuation for Ring Array Ultrasound Tomography Based on a Block LU Solver.

作者信息

Ali Rehman, Mitcham Trevor M, Brevett Thurston, Agudo Oscar Calderon, Martinez Cristina Duran, Li Cuiping, Doyley Marvin M, Duric Nebojsa

出版信息

IEEE Trans Med Imaging. 2024 Aug;43(8):2988-3000. doi: 10.1109/TMI.2024.3383816. Epub 2024 Aug 1.

DOI:10.1109/TMI.2024.3383816
PMID:38564345
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11294001/
Abstract

Ultrasound tomography is an emerging imaging modality that uses the transmission of ultrasound through tissue to reconstruct images of its mechanical properties. Initially, ray-based methods were used to reconstruct these images, but their inability to account for diffraction often resulted in poor resolution. Waveform inversion overcame this limitation, providing high-resolution images of the tissue. Most clinical implementations, often directed at breast cancer imaging, currently rely on a frequency-domain waveform inversion to reduce computation time. For ring arrays, ray tomography was long considered a necessary step prior to waveform inversion in order to avoid cycle skipping. However, in this paper, we demonstrate that frequency-domain waveform inversion can reliably reconstruct high-resolution images of sound speed and attenuation without relying on ray tomography to provide an initial model. We provide a detailed description of our frequency-domain waveform inversion algorithm with open-source code and data that we make publicly available.

摘要

超声层析成像术是一种新兴的成像方式,它利用超声波在组织中的传播来重建其力学特性的图像。最初,基于射线的方法被用于重建这些图像,但由于它们无法考虑衍射,常常导致分辨率较差。波形反演克服了这一局限性,能提供组织的高分辨率图像。目前,大多数临床应用(通常针对乳腺癌成像)常常依靠频域波形反演来减少计算时间。对于环形阵列,长期以来,射线层析成像被认为是波形反演之前的必要步骤,以避免周期跳跃。然而,在本文中,我们证明了频域波形反演可以可靠地重建声速和衰减的高分辨率图像,而无需依靠射线层析成像来提供初始模型。我们提供了频域波形反演算法的详细描述,并公开了开源代码和数据。