Information changes and time reversal for diffusion-related periodic fields

The resolution in photoacoustic imaging is limited by the acoustic bandwidth and therefore by acoustic attenuation, which can be substantial for high frequencies. This effect is usually ignored for photoacoustic reconstruction but has a strong influence on the resolution of small structures. The amount of information about the interior of samples, which can be gained in general by the detection of optical, thermal, or acoustical waves on the sample surface, is essentially influenced by the propagation from its excitation to the surface. Scattering, attenuation, and thermal diffusion cause an entropy production which results in a loss of information of propagating waves. Using a model based time reversal method, it was possible to partly compensate acoustic attenuation in photoacoustic imaging. To examine this loss of information in more detail, we have restricted us to "thermal waves" in one dimension, which can be realized experimentally by planar layers. Simulations using various boundary conditions and experimental results are compared. Reconstruction of the initial temperature profile from measurement data is performed by various regularization methods, the influence of the measurement noise (fluctuations) on the information loss during reconstruction is shown to be equal to the entropy production during wave propagation.

[1]  M. Haltmeier,et al.  Exact and approximative imaging methods for photoacoustic tomography using an arbitrary detection surface. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Eugène Dieulesaint,et al.  Elastic Waves in Solids II , 2000 .

[3]  L. Trefethen Spectral Methods in MATLAB , 2000 .

[4]  Lihong V. Wang,et al.  Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging , 2006, Nature Biotechnology.

[5]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[6]  Xu Xiao Photoacoustic imaging in biomedicine , 2008 .

[7]  A. Tikhonov On the stability of inverse problems , 1943 .

[9]  A. Mandelis,et al.  Experimental and image-inversion optimization aspects of thermal-wave diffraction tomographic microscopy. , 2000, Optics express.

[10]  E. Villaseñor Introduction to Quantum Mechanics , 2008, Nature.

[11]  Robert Nuster,et al.  Compensation of acoustic attenuation for high-resolution photoacoustic imaging with line detectors , 2007, SPIE BiOS.

[12]  P. Mazur,et al.  Non-equilibrium thermodynamics, , 1963 .

[13]  Vladimir Aleksandrovich Shutilov,et al.  Fundamental Physics of Ultrasound , 1988 .

[14]  George Gabriel Stokes,et al.  Mathematical and Physical Papers vol.1: On the Theories of the Internal Friction of Fluids in Motion, and of the Equilibrium and Motion of Elastic Solids , 2009 .

[15]  Per Christian Hansen,et al.  Rank-Deficient and Discrete Ill-Posed Problems , 1996 .

[16]  Patrick J La Rivière,et al.  Image reconstruction in optoacoustic tomography for dispersive acoustic media. , 2006, Optics letters.

[17]  Per Christian Hansen,et al.  Analysis of Discrete Ill-Posed Problems by Means of the L-Curve , 1992, SIAM Rev..