We establish inversion formulas of the so called filtered back-projection type to recover a function supported in the ball in even dimensions from its spherical means over spheres centered on the boundary of the ball. We also find several formulas to recover initial data of the from (f, 0) (or (0, g)) for the free space wave equation in even dimensions from the trace of the solution on the boundary of the ball, provided the initial data has support in the ball.

No abstract

Two universal reconstruction methods for photoacoustic (also called optoacoustic or thermoacoustic) computed tomography are derived, applicable to an arbitrarily shaped detection surface. In photoacoustic tomography acoustic pressure waves are induced by illuminating a semitransparent sample with pulsed electromagnetic radiation and are measured on a detection surface outside the sample. The imaging problem consists in reconstructing the initial pressure sources from those measurements. The first solution to this problem is based on the time reversal of the acoustic pressure field with a second order embedded boundary method. The pressure on the arbitrarily shaped detection surface is set to coincide with the measured data in reversed temporal order. In the second approach the reconstruction problem is solved by calculating the far-field approximation, a concept well known in physics, where the generated acoustic wave is approximated by an outgoing spherical wave with the reconstruction point as center. Numerical simulations are used to compare the proposed universal reconstruction methods with existing algorithms.

Motivated by the theoretical and practical results in compressed sensing, efforts have been undertaken by the inverse problems community to derive analogous results, for instance linear convergence rates, for Tikhonov regularization with 1 -penalty term for the solution of ill-posed equations. Conceptually, the main difference between these two fields is that regularization in general is an unconstrained optimization problem, while in compressed sensing a constrained one is used. Since the two methods have been developed in two different communities, the theoretical approaches to them appear to be rather different: In compressed sensing, the restricted isometry property seems to be central for proving linear convergence rates, whereas in regularization theory range or source conditions are imposed. The paper gives a common meaning to the seemingly different conditions and puts them into perspective with the conditions from the respective other community. A particularly important observation is that the range condition together with an injectivity condition is weaker than the restricted isometry property. Under the weaker conditions, linear convergence rates can be proven for compressed sensing and for Tikhonov regularization. Thus existing results from the literature can be improved based on a unified analysis. In particular, the range condition is shown to be the weakest possible condition that permits the derivation of linear convergence rates for Tikhonov regularization with a priori parameter choice.

A three-dimensional photoacoustic imaging method is presented that uses a Mach-Zehnder interferometer for measurement of acoustic waves generated in an object by irradiation with short laser pulses. The signals acquired with the interferometer correspond to line integrals over the acoustic wave field. An algorithm for reconstruction of a three-dimensional image from such signals measured at multiple positions around the object is shown that is a combination of a frequency-domain technique and the inverse Radon transform. From images of a small source scanning across the interferometer beam it is estimated that the spatial resolution of the imaging system is in the range of 100 to about 300 mum, depending on the interferometer beam width and the size of the aperture formed by the scan length divided by the source-detector distance. By taking an image of a phantom it could be shown that the imaging system in its present configuration is capable of producing three-dimensional images of objects with an overall size in the range of several millimeters to centimeters. Strategies are proposed how the technique can be scaled for imaging of smaller objects with higher resolution.