انتشارات / RCBTR
تاریخ: 2020/03/22
توسط: Dr Alireza Ahmadian
منتشر شده در: Biomedical Optics Express
فایل های پیوست:
URL منتشر شده: https://www.researchgate.net/publication/340024739_A_Dictionary_Learning_Technique_Enhances_Signal_in_LED-based_Photoacoustic_Imaging

Parastoo Farnia, Ebrahim Najafzadeh, Ali Hariri, Saeedeh Navaei Lavasani, Bahador Makkiabadi, Alireza Ahmadian, and Jesse V. Jokerst

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 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 signal. The main improvements of this approach are a 38% higher contrast ratio and a 43% higher axial resolution versus 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.