A Deep Learning-Based Model That Reduces Speed of Sound Aberrations for Improved In Vivo Photoacoustic Imaging

Abstract

Photoacoustic imaging (PAI) has attracted great attention as a medical imaging method. Typically, photoacoustic (PA) images are reconstructed via beamforming, but many factors still hinder the beamforming techniques in reconstructing optimal images in terms of image resolution, imaging depth, or processing speed. Here, we demonstrate a novel deep learning PAI that uses multiple speed of sound (SoS) inputs. With this novel method, we achieved SoS aberration mitigation, streak artifact removal, and temporal resolution improvement all at once in structural and functional in vivo PA images of healthy human limbs and melanoma patients. The presented method produces high-contrast PA images in vivo with reduced distortion, even in adverse conditions where the medium is heterogeneous and/or the data sampling is sparse. Thus, we believe that this new method can achieve high image quality with fast data acquisition and can contribute to the advance of clinical PAI.

Adaptive dual-speed ultrasound and photoacoustic computed tomography

“…To determine the correct sound speed in the sample, we search the maximum coherence factor (CF) of the US signals at different sample SoS values. Firstly, we use a multi-stencil fast marching (MSFM) method to calculate a series of time of flight (ToF) maps under different sample SoS values (Step 5) [27] . The MSFM method considers the acoustic refraction in the propagation path and calculates the shortest ToF between the transducer element and the reconstructed pixel by solving the eikonal equation [28] , [29] , where is the ToF at the reconstructed pixel ( ).…”

Fully integrated photoacoustic microscopy and photoplethysmography of human in vivo

“…In addition, PAI enables multiscale imaging from microscopy to clinical applications, depending on which optical and ultrasonic subsystems are combined [9] , [10] , [11] , [12] , [13] , [14] , [15] . Most clinical studies have been conducted in the form of photoacoustic tomography with a high intensity pulsed laser and medical ultrasound machines that are widely used in hospitals and clinics [16] , [17] , [18] , [19] . As another form of PAI, photoacoustic microscopy (PAM) is effective at high-resolution imaging by tightly focusing light [20] .…”

Photoacoustic imaging systems based on clinical ultrasound platform

“…The generated PA waves are detected by conventional ultrasound (US) transducers and then reconstructed as images through digital signal and image processing algorithms. 4–8…”

“…The generated PA waves are detected by conventional ultrasound (US) transducers and then reconstructed as images through digital signal and image processing algorithms. [4][5][6][7][8] Regarding the principles of PAI, the data acquisition and image reconstruction parts are identical to those used for USI. Therefore, it is common to combine the two modalities…”