A Comparative Study of Time Domain Compressed Sensing Techniques for Optoacoustic Imaging

Authors

Keywords:

optoacoustic imaging, compressed sensing, time domain models, reconstruction algorithms

Abstract

Speeding up data acquisition and reducing the complexity of the detection system are among the central goals for advancing optoacoustic imaging. In this way, new reconstruction algorithms using the compressed sensing (CS) formalism have received considerable interest in recent years. This work presents a comparative study of reconstruction algorithms using time-domain CS schemes for optoacoustic tomography. This is motivated by the well-known capabilities of the CS paradigm in achieving good reconstruction performance even with limited sensing capabilities. Formulation of the mathematical problem is provided along with simulation results, where the performance of different representation basis used in time-domain CS strategies are analyzed in a qualitative and quantitative fashion. Comparison with a well-established optoacoustic tomography reconstruction technique as backprojection is also provided. These experiments show the suitability of time-domain CS techniques for this application and point out that the use of the canonical basis for the representation of the optoacoustic measurements is well suited in comparison with other more sophisticated basis.

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Author Biographies

Lucas Hirsch, Facultad de Ingeniería, Universidad de Buenos Aires

He was born in Buenos Aires, Argentina. He received the M.Sc degree in Electrical Engineering from the University of Buenos Aires (UBA) in 2021, where he is currently a teaching assitant. His research interests include photoacoustic imaging, signal processing and artificial intelligence.

Martin German Gonzalez, Facultad de Ingeniería, Universidad de Buenos Aires

He was born in Buenos Aires, Argentina. He received the M.Sc and PhD degrees in Electrical Engineering from the UBA, in 2003 and 2008, respectively. In 2009 and 2010, he was a postdoctoral researcher at the Technische Universität München, Germany. Currently, he is a Professor at UBA and a research fellow at CONICET, Argentina. His research interests include optoacoustic imaging, ultrasonic sensors and artificial intelligence.

Leonardo Rey Vega, Facultad de Ingeniería, Universidad de Buenos Aires, CONICET

He received the M.Sc and PhD degrees in Electrical Engineering from the UBA in 2004 and 2010, respectively. In 2007 and 2008 he was invited at the INRS-EMT in Montreal, Canada. He is currently a Professor at the UBA and member of CONICET. His research interests include statistical signal processing, information theory, representation learning and wireless sensor networks.

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Published

2022-04-05

How to Cite

Hirsch, L., Gonzalez, M. G., & Rey Vega, L. (2022). A Comparative Study of Time Domain Compressed Sensing Techniques for Optoacoustic Imaging. IEEE Latin America Transactions, 20(6), 1018–1024. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/6247