A coordinate ascent approach to tomographic reconstruction of label images from a few projections

Our aim is to produce a tessellation of space into small voxels and, based on only a few tomographic projections of an object, assign to each voxel a label from a small predetermined set that indicates one of the components of interest constituting the object. Traditional methods are not reliable due to, among other reasons, the low number of projections. We postulate a low level prior knowledge regarding the underlying distribution of label images, and then directly estimate a label image based on the prior and the projections. We use a coordinate ascent approach for the estimation.