Photoacoustic tomography of heterogenous media using a model-based time reversal method

被引:7
作者
Gruen, Hubert [1 ]
Nuster, Robert [2 ]
Paltauf, Guenther [2 ]
Haltmeier, Markus [3 ]
Burgholzer, Peter [1 ]
机构
[1] Upper Austrian Res GmbH, Hafenstr 47-51, A-4020 Linz, Austria
[2] Karl Franzens Univ Graz, A-8010 Graz, Austria
[3] Leopold Franzens Univ, A-6020 Innsbruck, Austria
来源
PHOTONS PLUS ULTRASOUND: IMAGING AND SENSING 2008: THE NINTH CONFERENCE ON BIOMEDICAL THERMOACOUSTICS, OPTOACOUSTICS, AND ACOUSTIC-OPTICS | 2008年 / 6856卷
基金
奥地利科学基金会;
关键词
photoacoustic tomography; inhomogeneities; time reversal reconstruction;
D O I
10.1117/12.763111
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
In photoacoustic (also called optoacoustic or thermoacoustic) tomography acoustic pressure waves are generated by illumination of a semitransparent sample with pulsed electromagnetic radiation. Subsequently the waves propagate toward the detection surface enclosing the sample. The inverse problem consists of reconstructing the initial pressure sources from those measurements. By combining the high spatial resolution of ultrasonic imaging with the high contrast of optical imaging it offers new potentials in medical diagnostics. In certain applications of photoacoustic imaging one has to deal with media with spatially varying sound velocity, e.g. bones in soft tissue. These inhomogeneities have a strong influence on the propagation of photoacoustically generated sound waves. Image reconstruction without any compensation of this effect leads to a poor image quality. It is therefore essential to develop reconstruction algorithms that take spatially varying sound velocity into account and are able to reveal small structures in acoustically heterogeneous media. A model-based time reversal reconstruction method is presented that is capable of reconstructing the initial pressure distribution despite variations of sound speed. This reconstruction method calculates the time reversed field directly with a second order embedded boundary method by retransmitting the measured pressure on the detector positions in reversed temporal order. With numerical simulations the effect of heterogenous media on sound propagation and the consequences for image reconstruction without compensation are shown. It is demonstrated how time reversal can lead to a correct reconstruction if the distribution of sound speed is known. Corresponding experiments with phantoms consisting of areas with spatially varying sound velocity are carried out and the algorithm is applied to the measured signals.
引用
收藏
页数:9
相关论文
共 50 条
  • [31] The photoacoustic computed tomography of bones and joints using the system based on PCI4732
    Zhong, X. C.
    Jing, X. Y.
    Huang, L.
    Rong, J.
    Li, T. T.
    Gao, Y.
    INFORMATION TECHNOLOGY AND COMPUTER APPLICATION ENGINEERING, 2014, : 661 - 663
  • [32] Fingerprinting Inhomogeneities in Recording Media Using the First-Order Reversal Curve Method
    Valcu, Bogdan F.
    Gilbert, Dustin A.
    Liu, Kai
    IEEE TRANSACTIONS ON MAGNETICS, 2011, 47 (10) : 2988 - 2991
  • [33] Model-based tomographic optoacoustic reconstruction in media with small speed of sound variations
    Dean-Ben, X. Luis
    Ntziachristos, Vasilis
    Razansky, Daniel
    PHOTONS PLUS ULTRASOUND: IMAGING AND SENSING 2013, 2013, 8581
  • [34] Spatially variant regularization based on model resolution and fidelity embedding characteristics improves photoacoustic tomography
    Sanny, Dween Rabius
    Prakash, Jaya
    Kalva, Sandeep Kumar
    Pramanik, Manojit
    Yalavarthy, Phaneendra K.
    JOURNAL OF BIOMEDICAL OPTICS, 2018, 23 (10)
  • [35] Full-Wave Image Reconstruction in Transcranial Photoacoustic Computed Tomography Using a Finite Element Method
    Luo, Yilin
    Huang, Hsuan-Kai
    Sastry, Karteekeya
    Hu, Peng
    Tong, Xin
    Kuo, Joseph
    Aborahama, Yousuf
    Na, Shuai
    Villa, Umberto
    Anastasio, Mark. A.
    Wang, Lihong V.
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2025, 44 (02) : 645 - 655
  • [36] Full-view photoacoustic tomography using asymmetric distributed sensors optimized with compressed sensing method
    Cao, Meng
    Yuan, Jie
    Du, Sidan
    Xu, Guan
    Wang, Xueding
    Carson, Paul L.
    Liu, Xiaojun
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2015, 21 : 19 - 25
  • [37] Virtual compressed sensing photoacoustic tomography using BPDN algorithm based on k-space
    Wang, Jing
    Li, Bo
    Zhao, Aojie
    Song, Xianlin
    DIGITAL OPTICAL TECHNOLOGIES 2021, 2021, 11788
  • [38] Model-based temporal unmixing towards quantitative photo-switching optoacoustic tomography
    Liu, Yan
    Chuah, Jonathan
    Huang, Yishu
    Stiel, Andre c.
    Unser, Michael
    Dong, Jonathan
    OPTICS EXPRESS, 2025, 33 (03): : 6216 - 6227
  • [39] Fast Semi-Analytical Model-Based Acoustic Inversion for Quantitative Optoacoustic Tomography
    Rosenthal, Amir
    Razansky, Daniel
    Ntziachristos, Vasilis
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2010, 29 (06) : 1275 - 1285
  • [40] Ultra-sparse reconstruction for photoacoustic tomography: Sinogram domain prior-guided method exploiting enhanced score-based diffusion model
    Li, Zilong
    Lin, Jiabin
    Wang, Yiguang
    Li, Jiahong
    Cao, Yubin
    Liu, Xuan
    Wan, Wenbo
    Liu, Qiegen
    Song, Xianlin
    PHOTOACOUSTICS, 2025, 41