This book presents the development and application of regularized statistical methods for the analysis of anatomical structures. One of the comprehensive goals of this type of research is to use non-invasive medical imaging devices for the detection of diseases which are otherwise difficult to diagnose at an early stage. Statistics represents a quintessential part of such investigations as they are preluded by a clinical hypothesis that must be verified based on observed data. The massive amounts of image data produced in each examination pose an important and interesting statistical challenge, in that there are many more image features (variables) than subjects (observations), making an infinite number of solutions possible. To arrive at a unique and interesting answer, the analysis must be regularized in a sensible manner. This book describes such regularization options, discusses efficient algorithms which make the analysis of large data sets feasible, and gives examples of applications.

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