Combating acoustic heterogeneity in photoacoustic computed tomography:A review

Based on the energy conversion of light into sound,photoacoustic computed tomography(PACT)is an emerging biomedical imaging modality and has unique applications in a range of biomedical fields.In PACT,image formation relies on a process called acoustic inversion from received photoacoustic signals.While most PACT systems perform this inversion with a basic assumption that biological tissues are acoustically homogeneous,the community gradually rea-lizes that the intrinsic acoustic heterogeneity of tissues could pose distortions and artifacts to finally formed images.This paper surveys the most recent research progress on acoustic het-erogeneity correction in PACT.Four major strategies are reviewed in detail,including half-time or partial-time reconstruction,autofocus reconstruction by optimizing sound speed maps,joint reconstruction of optical absorption and sound speed maps,and ultrasound computed tomog-raphy(USCT)enhanced reconstruction.The correction of acoustic heterogeneity helps improve the imaging performance of PACT.

The sparse array elements selection in sparse imaging of circular-array photoacoustic tomography

Photoacoustic imaging(PAI)has been developed,and photoacoustic computed tomography(PACT)is widely used for in vivo tissue and mouse imaging.Simulated annealing(SA)algorithm solves optimization problems,and compressed sensing(CS)recovers sparse signals from undersampled measurements.We aim to develop an advanced sparse imaging framework for PACT,which invloves the use of SA to¯nd an optimal sparse array element distribution and CS to perform sparse imaging.PACT reconstructions were performed using a dummy and porcine liver phantoms.Compared to traditional sparse reconstruction algorithms,the proposed method recovers signals using few ultrasonic transducer elements,enabling high-speed,low-cost PACT for practical application.

Flexible fiber-laser ultrasound sensor for multiscale photoacoustic imaging

Photoacoustic imag ing(PAI)is a nonin vasive biomedical imag ing tech no logy capable of multiscale imag ing of biological samples from orga ns dow n to cells.Multiscale PAI requires differe nt ultraso und tra nsducers that are flat or focused because the current widely-used piezoelectric transducers are rigid and lack the flexibility to tune their spatial ultrasound responses.Inspired by the rapidly-developing flexible photonics,we exploited the inherent flexibility and low-loss features of optical fibers to develop a flexible fiber-laser ultrasound sensor(FUS)for multiscale PAI.By simply bending the fiber laser from straight to curved geometry,the spatial ultraso und resp onse of the FUS can be tuned for both wide-view optical-resolution photoacoustic microscopy at optical diffraction-limited depth(~1 mm)and photoacoustic computed tomography at optical dissipation-limited depth of several centimeters.A radio-frequency demodulation was employed to get the readout of the beat frequency variation of two orthogonal polarization modes in the FUS output,which ensures low-noise and stable ultrasound detection.Compared to traditional piezoelectrical transducers with fixed ultrasound responses once manufactured,the flexible FUS provides the freedom to design multiscale PAI modalities including wearable microscope,intravascular endoscopy,and portable tomography system,which is attractive to fundamental biologic-al/medical studies and clinical applications.

Optimizing photoacoustic image reconstruction using cross-platform parallel computation

Three-dimensional(3D)image reconstruction involves the computations of an extensive amount of data that leads to tremendous processing time.Therefore,optimization is crucially needed to improve the performance and efficiency.With the widespread use of graphics processing units(GPU),parallel computing is transforming this arduous reconstruction process for numerous imaging modalities,and photoacoustic computed tomography(PACT)is not an exception.Existing works have investigated GPU-based optimization on photoacoustic microscopy(PAM)and PACT reconstruction using compute unified device architecture(CUDA)on either C++or MATLAB only.However,our study is the first that uses cross-platform GPU computation.It maintains the simplicity of MATLAB,while improves the speed through CUDA/C++−based MATLAB converted functions called MEXCUDA.Compared to a purely MATLAB with GPU approach,our cross-platform method improves the speed five times.Because MATLAB is widely used in PAM and PACT,this study will open up new avenues for photoacoustic image reconstruction and relevant real-time imaging applications.