Dictionary Learning Technique Enhances Signal in Led-Based Photoacoustic Imaging Publisher



Farnia P^{1, 2} ; Najafzadeh E^{1, 2} ; Hariri A³ ; Lavasani SN^{2, 4} ; Makkiabadi B^{1, 2} ; Ahmadian A^{1, 2} ; Jokerst JV^{3, 5, 6} Show Affiliations
Source: Biomedical Optics Express Published:2020

Abstract

There has been growing interest in low-cost light sources such as light-emitting diodes (LEDs) as an excitation source in photoacoustic imaging. However, LED-based photoacoustic imaging is limited by low signal due to low energy per pulse—the signal is easily buried in noise leading to low quality images. Here, we describe a signal de-noising approach for LED-based photoacoustic signals based on dictionary learning with an alternating direction method of multipliers. This signal enhancement method is then followed by a simple reconstruction approach delay and sum. This approach leads to sparse representation of the main components of the signal. The main improvements of this approach are a 38% higher contrast ratio and a 43% higher axial resolution versus the averaging method but with only 4% of the frames and consequently 49.5% less computational time. This makes it an appropriate option for real-time LED-based photoacoustic imaging. © 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.