Super-resolution photoacoustic imaging of sparse absorbers using L1-norm minimization (Conference Presentation)

David Egolf; Ryan Chee; Golam Chowdhury; Roger Zemp

doi:10.1117/12.2287204

15 March 2018 Super-resolution photoacoustic imaging of sparse absorbers using L1-norm minimization (Conference Presentation)

David Egolf, Ryan Chee, Golam Chowdhury, Roger Zemp

Author Affiliations +

Proceedings Volume 10494, Photons Plus Ultrasound: Imaging and Sensing 2018; 104942R (2018) https://doi.org/10.1117/12.2287204
Event: SPIE BiOS, 2018, San Francisco, California, United States

Abstract

Delay and sum beamformed acoustic-resolution photoacoustic images are limited in resolution by the wavelength of the received acoustic signal. We seek to improve on this resolution in the case when the received signal is known to be generated by only a few absorbers. When the absorbers to be imaged are known a priori to be sparse then the reconstruction problem can be stated as an optimization problem aiming to minimize the residual between model predictions and measured channel data and also an L1-norm-based metric of sparsity. In brief, the strategy aims to express experimentally observed curved wavefronts in channel data as a super-position of simulated point-spread functions with a constraint on sparsity. The approach is similar in spirit to recent super-resolution contrast ultrasound approaches but uses an L1-norm minimization strategy. We have applied this optimization strategy to photoacoustic beamforming in both simulation and experiment. Simulation was conducted using Field II, and an experimental measure of resolving power was obtained by imaging the cross section of two wires at successively smaller separations. Experimental channel data was acquired using a 21-MHz Visualsonics array transducers with a Verasonics Vantage ultrasound platform for data acquisition. Simulations indicate potential to beat the ultrasound diffraction limit by a factor of four or more while current experiments achieve a factor of two resolution improvement. A possible application of this approach is for providing increased resolution images of the microvasculature surrounding cancerous tumors. Ongoing work aims to investigate in vivo performance of the proposed sparsity-constrained super-resolution approach.

Conference Presentation

Citation Download Citation

David Egolf, Ryan Chee, Golam Chowdhury, and Roger Zemp "Super-resolution photoacoustic imaging of sparse absorbers using L1-norm minimization (Conference Presentation)", Proc. SPIE 10494, Photons Plus Ultrasound: Imaging and Sensing 2018, 104942R (15 March 2018); https://doi.org/10.1117/12.2287204

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