Dynamic tomography using curve evolution with spatial-temporal regularization

We develop a variational method for dynamic tomography using curve evolution with spatial-temporal regularization. We take into account both the dynamics of the object boundaries as well as the dynamics of region intensities. These quantities are jointly estimated through minimization of an appropriately defined energy function. The temporal correlation of the object boundary curves are included through a weighted area difference distance measure between curves. The intensity dynamics are captured through a simple autoregressive model. Curve evolution methods are used to solve for the optimal reconstruction, which are implemented with efficient level set techniques. The strength of this approach is demonstrated through the successful reconstruction of an object sequence based on observations of only a single projection angle over time.