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      Image restoration for ring-array photoacoustic tomography system based on blind spatially rotational deconvolution

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          Abstract

          Ring-array photoacoustic tomography (PAT) system has been widely used in noninvasive biomedical imaging. However, the reconstructed image usually suffers from spatially rotational blur and streak artifacts due to the non-ideal imaging conditions. To improve the reconstructed image towards higher quality, we propose a concept of spatially rotational convolution to formulate the image blur process, then we build a regularized restoration problem model accordingly and design an alternating minimization algorithm which is called blind spatially rotational deconvolution to achieve the restored image. Besides, we also present an image preprocessing method based on the proposed algorithm to remove the streak artifacts. We take experiments on phantoms and in vivo biological tissues for evaluation, the results show that our approach can significantly enhance the resolution of the image obtained from ring-array PAT system and remove the streak artifacts effectively.

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          Most cited references66

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          Photoacoustic tomography: in vivo imaging from organelles to organs.

          Photoacoustic tomography (PAT) can create multiscale multicontrast images of living biological structures ranging from organelles to organs. This emerging technology overcomes the high degree of scattering of optical photons in biological tissue by making use of the photoacoustic effect. Light absorption by molecules creates a thermally induced pressure jump that launches ultrasonic waves, which are received by acoustic detectors to form images. Different implementations of PAT allow the spatial resolution to be scaled with the desired imaging depth in tissue while a high depth-to-resolution ratio is maintained. As a rule of thumb, the achievable spatial resolution is on the order of 1/200 of the desired imaging depth, which can reach up to 7 centimeters. PAT provides anatomical, functional, metabolic, molecular, and genetic contrasts of vasculature, hemodynamics, oxygen metabolism, biomarkers, and gene expression. We review the state of the art of PAT for both biological and clinical studies and discuss future prospects.
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            Nonlinear total variation based noise removal algorithms

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              A practical guide to photoacoustic tomography in the life sciences.

              The life sciences can benefit greatly from imaging technologies that connect microscopic discoveries with macroscopic observations. One technology uniquely positioned to provide such benefits is photoacoustic tomography (PAT), a sensitive modality for imaging optical absorption contrast over a range of spatial scales at high speed. In PAT, endogenous contrast reveals a tissue's anatomical, functional, metabolic, and histologic properties, and exogenous contrast provides molecular and cellular specificity. The spatial scale of PAT covers organelles, cells, tissues, organs, and small animals. Consequently, PAT is complementary to other imaging modalities in contrast mechanism, penetration, spatial resolution, and temporal resolution. We review the fundamentals of PAT and provide practical guidelines for matching PAT systems with research needs. We also summarize the most promising biomedical applications of PAT, discuss related challenges, and envision PAT's potential to lead to further breakthroughs.
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                Author and article information

                Contributors
                Journal
                Photoacoustics
                Photoacoustics
                Photoacoustics
                Elsevier
                2213-5979
                16 April 2024
                August 2024
                16 April 2024
                : 38
                : 100607
                Affiliations
                [a ]College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 211106, China
                [b ]Key Laboratory of Space Photoelectric Detection and Perception (Nanjing University of Aeronautics and Astronautics), Ministry of Industry and Information Technology, Nanjing, Jiangsu 211106, China
                [c ]School of Engineering Science, University of Science and Technology of China, Hefei, Anhui 230026, China
                [d ]School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China
                [e ]Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, Anhui 230088, China
                [f ]Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing, Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, Anhui 230088, China
                Author notes
                [* ]Corresponding author at: School of Engineering Science, University of Science and Technology of China, Hefei, Anhui 230026, China. ctian@ 123456ustc.edu.cn
                Article
                S2213-5979(24)00024-7 100607
                10.1016/j.pacs.2024.100607
                11044036
                38665365
                fe47cfdc-ddbc-4dc9-9a7c-5d20f81fe27a
                © 2024 The Authors

                This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

                History
                : 29 December 2023
                : 17 March 2024
                : 9 April 2024
                Categories
                Research Article

                photoacoustic tomography,image restoration,deconvolution,streak artifacts

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