Image Reconstruction Using Iterative Transpose Algorithm for Optical Tomography

This paper describes a transpose algorithm for use with an optical tomography system. the measurement system consisted of two orthogonal arrays, each having ten parallel views, resulting in a total of twenty sensors. the measurement section is divided into hundred equi–sized pixels. the forward problem is modelled by allocating an optical attenuation coefficient to each pixel. the attenuation of incident collimated light beams is then modelled using the lambert–beer law. the inverse problem is defined and the transpose of the sensitivity matrix is used to obtain an estimate of the attenuation coefficients in each pixel. the iterative method is investigated as a means of improving reconstructed image quality