In tomographic imaging, information on inner structures of a measured object is obtained indirectly by reconstructing an image of the object from its projections. In theory, image reconstruction is an ill-posed problem making it challenging in practice. The problem is trickier if some of the projections are missing, such as in limited-view tomography; or if the data are corrupted by object motion during the acquisition, as can happen in medical applications. The conventional way to treat these problems is to reconstruct the projections before further processing. In this book, we concentrate on a novel mathematical stackgram approach to deal with these problems. The concept provides a technique to process the projection data prior to image reconstruction. The book is the first comprehensive work on the topic, providing insight into the approach and its use in tomographic imaging, and includes a compact, yet comprehensive, introductory part to image reconstruction and the applications in emission tomography. The book is targeted to readers who have a basic knowledge of signal processing or medical imaging. Also, the book includes original publications for scientific-oriented readers.

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