Variable speed of sound compensation in the linear-array photoacoustic tomography using a multi-stencils fast marching method

Abstract Despite the promising clinical application of linear-array photoacoustic tomography, it has been shown the variable speed of sound would severely affect the photoacoustic imaging quality, resulting in the target deterioration and inaccurate depth positioning in the conventional constant speed assumed delay and sum (DAS) reconstruction. By contrast, multi-stencils fast marching (MSFM) method is able to produce accurate time delay map for the tissue with inhomogeneous acoustic speed. This study explored the combination of DAS reconstruction algorithm with the MSFM approach to reduce the imaging distortions due to the speed spatial variation, where the target structure and target position in depth could be measured more precisely. To validate the performance of the proposed method, numerical, phantom, and in vivo photoacoustic studies were conducted with the qualitative and quantitative analysis, especially in the detection of mouse deep brain tumor with an intact skull.

[1]  Wiendelt Steenbergen,et al.  Speed-of-sound compensated photoacoustic tomography for accurate imaging. , 2012, Medical physics.

[2]  Chen Zhang,et al.  Efficient block-sparse model-based algorithm for photoacoustic image reconstruction , 2016, Biomed. Signal Process. Control..

[3]  Suhyun Park,et al.  Adaptive beamforming for photoacoustic imaging. , 2008, Optics letters.

[4]  Aly A. Farag,et al.  MultiStencils Fast Marching Methods: A Highly Accurate Solution to the Eikonal Equation on Cartesian Domains , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Lihong V. Wang,et al.  Photoacoustic Tomography: In Vivo Imaging from Organelles to Organs , 2012, Science.

[6]  Yi Shen,et al.  Monte Carlo light transport-based blood vessel quantification using linear array photoacoustic tomography , 2017 .

[7]  Daniel Razansky,et al.  Optoacoustic image segmentation based on signal domain analysis , 2015, Photoacoustics.

[8]  Xosé Luís Deán-Ben,et al.  Optimal self-calibration of tomographic reconstruction parameters in whole-body small animal optoacoustic imaging , 2014, Photoacoustics.

[9]  Da Xing,et al.  Fast photoacoustic imaging system based on 320-element linear transducer array. , 2004, Physics in medicine and biology.

[10]  Yi Shen,et al.  Compressive Sampling Photoacoustic Microscope System based on Low Rank Matrix Completion , 2016, Biomed. Signal Process. Control..

[11]  Sevan Harput,et al.  Spatial resolution and contrast enhancement in photoacoustic imaging with filter delay multiply and sum beamforming technique , 2016, 2016 IEEE International Ultrasonics Symposium (IUS).

[12]  Huabei Jiang,et al.  Three-dimensional finite-element-based photoacoustic tomography: reconstruction algorithm and simulations. , 2007, Medical physics.

[13]  Ali Mahloojifar,et al.  Double-Stage Delay Multiply and Sum Beamforming Algorithm: Application to Linear-Array Photoacoustic Imaging , 2018, IEEE Transactions on Biomedical Engineering.

[14]  Jin Ho Chang,et al.  Enhancement of photoacoustic image quality by sound speed correction: ex vivo evaluation. , 2012, Optics express.

[15]  Jan Laufer,et al.  Quantitative determination of chromophore concentrations from 2D photoacoustic images using a nonlinear model-based inversion scheme. , 2010, Applied optics.

[16]  Srirang Manohar,et al.  Quantitative photoacoustic tomography by stochastic search: direct recovery of the optical absorption field. , 2016, Optics letters.

[17]  Ichiro Sakuma,et al.  Phase aberration correction by multi-stencils fast marching method using sound speed image in ultrasound computed tomography , 2016, SPIE Medical Imaging.

[18]  Robert A Kruger,et al.  Thermoacoustic computed tomography using a conventional linear transducer array. , 2003, Medical physics.

[19]  Hairong Zheng,et al.  Biocompatible conjugated polymer nanoparticles for highly efficient photoacoustic imaging of orthotopic brain tumors in the second near-infrared window , 2017 .

[20]  B T Cox,et al.  k-Wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields. , 2010, Journal of biomedical optics.

[21]  Dimple Modgil,et al.  Image reconstruction in photoacoustic tomography with variable speed of sound using a higher-order geometrical acoustics approximation. , 2010, Journal of biomedical optics.

[22]  Kang Kim,et al.  Multi-Focus Beamforming for Thermal Strain Imaging Using a Single Ultrasound Linear Array Transducer. , 2017, Ultrasound in medicine & biology.

[23]  Sidan Du,et al.  Full-view photoacoustic tomography using asymmetric distributed sensors optimized with compressed sensing method , 2015, Biomed. Signal Process. Control..

[24]  Erwan Filoux,et al.  Coherence-weighted beamforming and automated vessel segmentation for improving photoacoustic imaging of embryonic vasculature using annular arrays , 2013, 2013 IEEE International Ultrasonics Symposium (IUS).

[25]  S. Arridge,et al.  Quantitative spectroscopic photoacoustic imaging: a review. , 2012, Journal of biomedical optics.

[26]  Geng Ku,et al.  Three-dimensional laser-induced photoacoustic tomography of mouse brain with the skin and skull intact. , 2003, Optics letters.

[27]  Wiendelt Steenbergen,et al.  Passive element enriched photoacoustic computed tomography (PER PACT) for simultaneous imaging of acoustic propagation properties and light absorption. , 2011, Optics express.

[28]  Yi Shen,et al.  Compressed sensing in synthetic aperture photoacoustic tomography based on a linear-array ultrasound transducer , 2017 .

[29]  C. Slump,et al.  Concomitant speed-of-sound tomography in photoacoustic imaging , 2007 .

[30]  R Gr Maev,et al.  Development of a practical ultrasonic approach for simultaneous measurement of the thickness and the sound speed in human skull bones: a laboratory phantom study , 2013, Physics in medicine and biology.