We apply and evaluate machine learning methods to obtain information purely from the tomographic projections of an image. We design and implement discrete tomographic reconstruction methods that can exploit the knowledge obtained in this way.

The goal of the project is to develop efficient image acquisition methods to gain visual information from incorrect, noisy, and uncertain projections.

This is the sample implementation of a MRF-based color image segmentation algorithm.