Photoacoustic image reconstruction in Bayesian framework

被引:0
|
作者
Tick, Jenni [1 ]
Pulkkinen, Aki [1 ]
Lucka, Felix [2 ,3 ]
Ellwood, Robert [4 ]
Cox, Ben T. [4 ]
Arridge, Simon R. [3 ]
Tarvainen, Tanja [1 ,3 ]
机构
[1] Univ Eastern Finland, Dept Appl Phys, POB 1627, Kuopio 70211, Finland
[2] Ctr Wiskunde & Informat, POB 94079, NL-1090 GB Amsterdam, Netherlands
[3] UCL, Dept Comp Sci, Gower St, London WC1E 6BT, England
[4] UCL, Dept Med Phys & Biomed Engn, Gower St, London WC1E 6BT, England
基金
英国工程与自然科学研究理事会; 芬兰科学院;
关键词
photoacoustic tomography; inverse problems; Bayesian methods; TOMOGRAPHY; ALGORITHM; INVERSION;
D O I
10.1117/12.2288163
中图分类号
TH742 [显微镜];
学科分类号
摘要
The photoacoustic image reconstruction problem (inverse problem) is to estimate an initial acoustic pressure distribution from measurements of ultrasound waves generated within an object due to optical excitation with a short light pulse. In this work, the recently suggested Bayesian approach to photoacoustic tomography is extended to three dimensions and an iterative matrix-free method for the solution of the problem is described. Image reconstruction is investigated with numerical simulations and experimental data. The use of di ff erent prior information and noise models in di ff erent sensor geometries, including a limited-view setup, is investigated. The results show that the Bayesian approach can produce accurate estimates of the initial pressure distribution even in a limited-view setup provided that prior information and the noise have been properly modelled.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] Bayesian Image Reconstruction in Quantitative Photoacoustic Tomography
    Tarvainen, Tanja
    Pulkkinen, Aki
    Cox, Ben T.
    Kaipio, Jari P.
    Arridge, Simon R.
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2013, 32 (12) : 2287 - 2298
  • [2] Bayesian approach to image reconstruction in photoacoustic tomography
    Tick, Jenni
    Pulkkinen, Aki
    Tarvainen, Tanja
    [J]. PHOTONS PLUS ULTRASOUND: IMAGING AND SENSING 2017, 2017, 10064
  • [3] Photoacoustic image reconstruction based on Bayesian compressive sensing algorithm
    Sun, Mingjian
    Feng, Naizhang
    Shen, Yi
    Li, Jiangang
    Ma, Liyong
    Wu, Zhenghua
    [J]. CHINESE OPTICS LETTERS, 2011, 9 (06)
  • [4] A jointed feature fusion framework for photoacoustic image reconstruction
    Lan, Hengrong
    Yang, Changchun
    Gao, Fei
    [J]. PHOTOACOUSTICS, 2023, 29
  • [5] Photoacoustic image reconstruction based on Bayesian compressive sensing algorithm
    孙明健
    冯乃章
    沈毅
    李建刚
    马立勇
    伍政华
    [J]. Chinese Optics Letters, 2011, 9 (06) : 44 - 47
  • [6] Comprehensive framework of GPU-accelerated image reconstruction for photoacoustic computed tomography
    Wang, Yibing
    Li, Changhui
    [J]. JOURNAL OF BIOMEDICAL OPTICS, 2024, 29 (06)
  • [7] Three dimensional photoacoustic tomography in Bayesian framework
    Tick, Jenni
    Pulkkinen, Aki
    Lucka, Felix
    Ellwood, Robert
    Cox, Ben T.
    Kaipio, Jari P.
    Arridge, Simon R.
    Tarvainen, Tanja
    [J]. JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 2018, 144 (04): : 2061 - 2071
  • [8] Image Reconstruction in Intravascular Photoacoustic Imaging
    Sheu, Yae-lin
    Chou, Cheng-Ying
    Hsieh, Bao-Yu
    Li, Pai-Chi
    [J]. IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL, 2011, 58 (10) : 2067 - 2077
  • [9] Photoacoustic image reconstruction with uncertainty quantification
    Tick, J.
    Pulkkinen, A.
    Tarvainen, T.
    [J]. EMBEC & NBC 2017, 2018, 65 : 113 - 116
  • [10] Photoacoustic image reconstruction - A quantitative analysis
    Sperl, Jonathan I.
    Zell, Karin
    Menzenbach, Peter
    Haisch, Christoph
    Ketzer, Stephan
    Marquart, Markus
    Koenig, Hartmut
    Vogel, Mika W.
    [J]. NOVEL OPTICAL INSTRUMENTATION FOR BIOMEDICAL APPLICATIONS III, 2007, 6631