No abstract

Photoacoustic tomography (PAT) is a non-invasive imaging modality showing great potential in medical diagnosis and research due to its high optical contrast and high-resolution deep imaging. After laser irradiation on the tissue surface, energy absorption leads to the generation of acoustic waves (also known as PA waves), which can be collected by ultrasound detectors such as single-element ultrasound transducers (SUTs). A variety of image reconstruction algorithms can be employed to obtain the initial pressure distribution map. Previously, desktops or workstations are widely used for performing image-forming processes owing to their high computation power. But with the upgrade of mobile phones, they possess more and more powerful CPU or GPU, sometimes comparable to desktop computers. The capability of PAT can be further enhanced with the use of the mobile platform. In this work, we explored the usage of mobile platforms to reconstruct PAT images without sacrificing image quality. A mobile application was developed based on Python, implementing a simple delay-and-sum (DAS) beamformer for generating PAT images. HUAWEI P20 was employed to test the application performance, which spent less than 30 seconds to form a well-reconstructed PAT image with the SNR value more than 40 dB. Downsampling process can be performed, leading to much less reconstruction time while the photoacoustic target structure was still reconstructed properly, especially for two-fold downsampling operation. These results indicated that mobile platforms could support fast PAT image reconstruction and at the same time support good image quality.