Classification of digital angiograms using multipulse excited linear prediction model

A new automated method is presented for the classification of digital angiograms. The technique is based on approximating the given image by a two-dimensional linear prediction (LP) model along with a multipulse excitation sequence. The input to the synthesis filter is a stream of pulses, characterised by their location and amplitudes. The pulse parameters are estimated by minimizing a least squares problem. This results in a pulse pattern which traverses the contour of the dye in the angiogram. Excitation of the model by this multipulse sequence reconstructs the image containing only the dye profile. The correlation between multiple frames can be exploited in tracking the dye movements in time.