For high-resolution imaging of deep tissues, photoacoustic tomography (PAT) is a hybrid imaging method that combines ultrasound detection with optical illumination. Using the photoacoustic (Dad) impact, PAT furnishes an unmistakable benefit with versatile goals, higher imaging profundity, and high differentiation imaging. The tissue of interest is illuminated by nanosecond laser pulses, allowing its chromophores to absorb the incident laser energy. This results in a neighborhood temperature climb and produces pressure waves that proliferate to the tissue limit as ultrasound waves. Reconstruction algorithms are used to transform these PA waves into internal absorption maps after they are acquired with the assistance of an ultrasound transducer.
This course of producing starting strain guides can be done with a few different picture recreation calculations, including the basic postponement and total (DAS) beamformer. The acquired signals from various tissue locations are back-projected by this algorithm, which then adds them to each pixel of the reconstructed image. However, this results in artifacts, or anomalies, in the reconstructed images and makes the DAS beamformer computationally expensive and time-consuming. Despite these drawbacks, it is a popular choice for PAT reconstruction due to its simplicity and ease of use.
“The code for this Android-based application has been made freely available on GitHub, providing a significant service to the biomedical imaging community.”
JBO Editor-in-Chief Brian Pogue, Chair of Medical Physics at University of Wisconsin–Madison.
Regularly, executing such reproduction calculations requires a workstation, work area, or PC with broad computational assets. In any case, the computational force of cell phones has been increasing lately. Mobile phones have been suggested for a number of different types of microscopy, including ultrasound imaging, but their potential for photoacoustic imaging, like PAT image reconstruction, has not been investigated.
An Android-based application for PAT image reconstruction has been developed by researchers from Singapore and the United States, taking advantage of mobile phones’ advanced processing capabilities. Manojit Pramanik, a Northrop Grumman Associate Professor at Iowa State University’s Department of Electrical and Computer Engineering, was in charge of the study, which was published in the Journal of Biomedical Optics (JBO).
The created application uses a solitary component ultrasound transducer (SUT)-based DAS beamformer calculation for picture recreation on Kivy — a cross-stage Python 3.9.5 structure.
Using simulated and experimental PAT datasets, the researchers confirmed its performance on various mobile phones. The experimental datasets included a point source phantom, a triangular shape phantom, and blood vessels in the brains of live rats, in contrast to the simulated datasets’ point targets, triangular shape, and rat brain vessel shape.
Pramanik makes the following observation: “The developed application can successfully reconstruct the PAT data into high-quality PAT images with signal-to-noise ratio values above 30 decibels.”
Intriguingly, for small datasets, the algorithm’s computational time on a Huawei P20 phone was comparable to that on a laptop. In addition, image reconstruction was made possible with both speed and quality thanks to the original dataset’s two-fold downsampling, which reduced computation time while maintaining image quality. The PAT images, on the other hand, were clearly degraded by three-fold downsampling.
In addition, the scientists found that with the Samsung Universe S21+’s high-level processor, PAT remaking could be accomplished in just 2.4 seconds. “This is an extensively decreased running time for picture recreation and features the productivity of the cell phone application,” notes Pramanik.
“This first-of-its-kind application provides an opportunity for PAT image reconstruction on inexpensive, portable, and widely available mobile phones,” says JBO Editor-in-Chief Brian Pogue, Chair of Medical Physics at the University of Wisconsin-Madison. Going on, the application can make PAT frameworks more versatile and extendable to different fields of biomedical imaging, working with point-of-care analysis.” He adds, “This is a major service to the biomedical imaging community because the code for this Android-based application has been made freely available on GitHub.”
More information: Xie Hui et al, Android mobile-platform-based image reconstruction for photoacoustic tomography, Journal of Biomedical Optics (2023). DOI: 10.1117/1.JBO.28.4.046009
