Advances in Tomographic Imaging: the Stackgram Decomposition for Emission Data Processing

In tomographic imaging, information on innerstructures of a measured object is obtainedindirectly by reconstructing an image of the objectfrom its projections. In theory, image reconstructionis an ill-posed problem making it challenging inpractice. The problem is trickier if some of theprojections are missing, such as in limited-viewtomography; or if the data are corrupted by objectmotion during the acquisition, as can happen inmedical applications. The conventional way to treatthese problems is to reconstruct the projectionsbefore further processing. In this book, weconcentrate on a novel mathematical stackgramapproach to deal with these problems. The conceptprovides a technique to process the projection dataprior to image reconstruction. The book is the firstcomprehensive work on the topic, providing insightinto the approach and its use in tomographic imaging,and includes a compact, yet comprehensive,introductory part to image reconstruction and theapplications in emission tomography. The book istargeted to readers who have a basic knowledge ofsignal processing or medical imaging. Also, the bookincludes original publications forscientific-oriented readers.