  In practical applications of tomographic imaging, there are often challenges
for image reconstruction due to under-sampling and insufficient data. In
computed tomography (CT), for example, image reconstruction from few views
would enable rapid scanning with a reduced x-ray dose delivered to the patient.
Limited-angle problems are also of practical significance in CT. In this work,
we develop and investigate an iterative image reconstruction algorithm based on
the minimization of the image total variation (TV) that applies to
divergent-beam CT. Numerical demonstrations of our TV algorithm are performed
with various insufficient data problems in fan-beam CT. The TV algorithm can be
generalized to cone-beam CT as well as other tomographic imaging modalities.
