Limited angle tomography using regularized extrapolation technique

Considers the well-known limited angle or missing cone problem. The authors present an alternative method to extrapolate the missing set of projection data from limited angle of views without prior information of the scanning object, using two-dimensional sampling theory and the result by Rattey and Lindgren which shows that the spectral support of computerised tomography (CT) projection data is bowtie-shaped. A general matrix formulation is developed and the problem is posed as a least square optimization problem. This problem is then implemented by a nonstandard neural network. A novel training algorithm is proposed minimizing a modified error criterion. A computer simulation result is presented to demonstrate the validity of the algorithm