Maximum Entropy Based Non-Negative Optoacoustic Tomographic Image Reconstruction

被引:31
|
作者
Prakash, Jaya [1 ]
Mandal, Subhamoy [2 ,3 ]
Razansky, Daniel [2 ,4 ]
Ntziachristos, Vasilis [2 ,5 ]
机构
[1] Inst Biol & Med Imaging, Oberschleissheim, Germany
[2] Helmholtz Zentrum Munchen, Inst Biol & Med Imaging, D-85764 Munich, Germany
[3] Tech Univ Munich, Dept Elect & Comp Engn, Munich, Germany
[4] Tech Univ Munich, Sch Med, Munich, Germany
[5] Tech Univ Munich, Chair Biol Imaging, D-81675 Munich, Germany
基金
美国国家卫生研究院; 欧洲研究理事会;
关键词
Optical parameters; photoacoustic tomography; inverse problems; image reconstruction; regularization theory; PHOTOACOUSTIC TOMOGRAPHY; OPTICAL-ABSORPTION; REGULARIZATION; INVERSION; DISTRIBUTIONS; OXYGENATION; TISSUES;
D O I
10.1109/TBME.2019.2892842
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Objective: Optoacoustic (photoacoustic) tomography is aimed at reconstructing maps of the initial pressure rise induced by the absorption of light pulses in tissue. In practice, due to inaccurate assumptions in the forward model, noise, and other experimental factors, the images are often afflicted by artifacts, occasionally manifested as negative values. The aim of this work is to develop an inversion method which reduces the occurrence of negative values and improves the quantitative performance of optoacoustic imaging. Methods: We present a novel method for optoacoustic tomography based on an entropy maximization algorithm, which uses logarithmic regularization for attaining non-negative reconstructions. The reconstruction image quality is further improved using structural prior-based fluence correction. Results: We report the performance achieved by the entropy maximization scheme on numerical simulation, experimental phantoms, and in-vivo samples. Conclusion: The proposed algorithm demonstrates superior reconstruction performance by delivering non-negative pixel values with no visible distortion of anatomical structures. Significance: Our method can enable quantitative optoacoustic imaging, and has the potential to improve preclinical and translational imaging applications.
引用
收藏
页码:2604 / 2616
页数:13
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