A hierarchical feature based deformation model applied to 4D cardiac SPECT data

Abstract

In this paper we describe a statistical model for the observation of labeled points in gated cardiac single photon emission computed tomography (SPECT) images. The model has two major parts: one based on shape correspondence between the image for evaluation and a reference image, and a second based on the match in image features. While the statistical deformation model is applicable to a broad range of image objects, the addition of a contraction mechanism to the baseline model provides particularly convincing results in gated cardiac SPECT. The model is applied to clinical data and provides marked improvement in the quality of summary images for the time series. Estimates of heart deformation and contraction parameters are also obtained.