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离体模型中近骨软组织血管的光声成像

Photoacoustic Imaging of Near-Bone Soft Tissue Vasculature in an ex vivo Phantom.

作者信息

Wang Guessy C, Hix Jeremy M L, Tavelli Lorenzo, Yang Yang

机构信息

Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Ave, Boston, United States.

Department of Radiology and Institute for Quantitative Health Science and Engineering, Michigan State University, 775 Woodlot Dr, East Lansing, United States.

出版信息

Proc SPIE Int Soc Opt Eng. 2023 Feb;12468. doi: 10.1117/12.2653348. Epub 2023 Apr 10.

DOI:10.1117/12.2653348
PMID:40933883
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12419906/
Abstract

Photoacoustic imaging is an emerging preclinical modality that uses a combination of optics and acoustics mechanisms to visualize differences in optical absorption in target imaging objects. Photoacoustic imaging is potentially suitable for visualizing vasculature, as the hemoglobin in red blood cells is a prominent heat absorber and therefore serves as a great biomarker. Due to acoustic reflection, diffraction and scattering, photoacoustic imaging is subject to artifacts when the target soft tissue is close to bone. We construct an phantom featuring vascularized soft tissue near long bone, to facilitate evaluation of photoacoustic images and to enable future research on artifact removal in photoacoustic imaging.

摘要

光声成像是一种新兴的临床前成像模式,它利用光学和声学机制的组合来可视化目标成像对象中光吸收的差异。光声成像可能适用于血管成像,因为红细胞中的血红蛋白是一种显著的热吸收体,因此是一种很好的生物标志物。由于声反射、衍射和散射,当目标软组织靠近骨骼时,光声成像会产生伪影。我们构建了一个在长骨附近具有血管化软组织的体模,以促进光声图像的评估,并为未来光声成像中的伪影去除研究提供条件。

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本文引用的文献

1
A generative adversarial network for artifact removal in photoacoustic computed tomography with a linear-array transducer.一种基于线阵换能器的光声计算机断层成像中伪影去除的生成对抗网络。
Exp Biol Med (Maywood). 2020 Apr;245(7):597-605. doi: 10.1177/1535370220914285. Epub 2020 Mar 25.
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Photoacoustic-guided focused ultrasound (PAFUSion) for identifying reflection artifacts in photoacoustic imaging.用于在光声成像中识别反射伪像的光声引导聚焦超声(PAFUSion)。
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Biomed Opt Express. 2018 Sep 4;9(10):4613-4630. doi: 10.1364/BOE.9.004613. eCollection 2018 Oct 1.
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Photoacoustic Source Detection and Reflection Artifact Removal Enabled by Deep Learning.深度学习支持的光声源检测和反射伪影去除。
IEEE Trans Med Imaging. 2018 Jun;37(6):1464-1477. doi: 10.1109/TMI.2018.2829662.
5
In vivo demonstration of reflection artifact reduction in photoacoustic imaging using synthetic aperture photoacoustic-guided focused ultrasound (PAFUSion).使用合成孔径光声引导聚焦超声(PAFUSion)在体内证明光声成像中反射伪像的减少。
Biomed Opt Express. 2016 Jul 11;7(8):2955-72. doi: 10.1364/BOE.7.002955. eCollection 2016 Aug 1.
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Photoacoustic tomography: principles and advances.光声断层成像:原理与进展
Electromagn Waves (Camb). 2014;147:1-22. doi: 10.2528/pier14032303.
7
k-Wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields.k-Wave:用于模拟和重建光声波场的 MATLAB 工具箱。
J Biomed Opt. 2010 Mar-Apr;15(2):021314. doi: 10.1117/1.3360308.