Optical projection tomography via phase retrieval algorithms.

We describe a computational method for accurate, quantitative tomographic reconstructions in Optical Projection Tomography, based on phase retrieval algorithms. Our method overcomes limitations imposed by light scattering in opaque tissue samples under the memory effect regime, as well as reduces artifacts due to mechanical movements, misalignments or vibrations. We make use of Gerchberg-Saxton algorithms, calculating first the autocorrelation of the object and then retrieving the associated phase under four numerically simulated measurement conditions. By approaching the task in such a way, we avoid the projection alignment procedure, exploiting the fact that the autocorrelation sinogram is always aligned and centered. We thus propose two new, projection-based, tomographic imaging flowcharts that allow registration-free imaging of opaque biological specimens and unlock three-dimensional tomographic imaging of hidden objects. Two main reconstruction approaches are discussed in the text, focusing on their efficiency in the tomographic retrieval and discussing their applicability under four different numerical experiments.