Literature DB >> 27424604

High-speed, sparse-sampling three-dimensional photoacoustic computed tomography in vivo based on principal component analysis.

Jing Meng1, Zibo Jiang1, Lihong V Wang2, Jongin Park3, Chulhong Kim3, Mingjian Sun4, Yuanke Zhang1, Liang Song5.   

Abstract

Photoacoustic computed tomography (PACT) has emerged as a unique and promising technology for multiscale biomedical imaging. To fully realize its potential for various preclinical and clinical applications, development of systems with high imaging speed, reasonable cost, and manageable data flow are needed. Sparse-sampling PACT with advanced reconstruction algorithms, such as compressed-sensing reconstruction, has shown potential as a solution to this challenge. However, most such algorithms require iterative reconstruction and thus intense computation, which may lead to excessively long image reconstruction times. Here, we developed a principal component analysis (PCA)-based PACT (PCA-PACT) that can rapidly reconstruct high-quality, three-dimensional (3-D) PACT images with sparsely sampled data without requiring an iterative process. In vivo images of the vasculature of a human hand were obtained, thus validating the PCA-PACT method. The results showed that, compared with the back-projection (BP) method, PCA-PACT required ∼50% fewer measurements and ∼40% less time for image reconstruction, and the imaging quality was almost the same as that for BP with full sampling. In addition, compared with compressed sensing-based PACT, PCA-PACT had approximately sevenfold faster imaging speed with higher imaging accuracy. This work suggests a promising approach for low-cost, 3-D, rapid PACT for various biomedical applications.

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Mesh:

Year:  2016        PMID: 27424604     DOI: 10.1117/1.JBO.21.7.076007

Source DB:  PubMed          Journal:  J Biomed Opt        ISSN: 1083-3668            Impact factor:   3.170


  7 in total

1.  Dictionary learning sparse-sampling reconstruction method for in-vivo 3D photoacoustic computed tomography.

Authors:  Fangyan Liu; Xiaojing Gong; Lihong V Wang; Jingjing Guan; Liang Song; Jing Meng
Journal:  Biomed Opt Express       Date:  2019-03-05       Impact factor: 3.732

2.  Listening to tissues with new light: recent technological advances in photoacoustic imaging.

Authors:  Tri Vu; Daniel Razansky; Junjie Yao
Journal:  J Opt       Date:  2019-09-09       Impact factor: 2.516

3.  Video-rate high-resolution single-pixel nonscanning photoacoustic microscopy.

Authors:  Ningbo Chen; Jia Yu; Liangjian Liu; Zhiqiang Xu; Rongkang Gao; Tao Chen; Liang Song; Wei Zheng; Chengbo Liu
Journal:  Biomed Opt Express       Date:  2022-06-09       Impact factor: 3.562

Review 4.  Advanced optoacoustic methods for multiscale imaging of in vivo dynamics.

Authors:  X L Deán-Ben; S Gottschalk; B Mc Larney; S Shoham; D Razansky
Journal:  Chem Soc Rev       Date:  2017-04-18       Impact factor: 54.564

Review 5.  Review of cost reduction methods in photoacoustic computed tomography.

Authors:  Afreen Fatima; Karl Kratkiewicz; Rayyan Manwar; Mohsin Zafar; Ruiying Zhang; Bin Huang; Neda Dadashzadeh; Jun Xia; Kamran Mohammad Avanaki
Journal:  Photoacoustics       Date:  2019-07-26

6.  Single-pixel camera photoacoustic tomography.

Authors:  Nam Huynh; Felix Lucka; Edward Zhang; Marta Betcke; Simon R Arridge; Paul C Beard; Benjamin T Cox
Journal:  J Biomed Opt       Date:  2019-09       Impact factor: 3.170

7.  Optoacoustic micro-tomography at 100 volumes per second.

Authors:  X Luís Deán-Ben; Hernán López-Schier; Daniel Razansky
Journal:  Sci Rep       Date:  2017-07-31       Impact factor: 4.379

  7 in total

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