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Imaging Genetics presents the latest research in imaging genetics methodology for discovering new associations between imaging and genetic variables, providing an overview of the state-of the-art in the field. Edited and written by leading researchers, this book is a beneficial reference for students and researchers, both new and experienced, in this growing area. The field of imaging genetics studies the relationships between DNA variation and measurements derived from anatomical or functional imaging data, often in the context of a disorder. While traditional genetic analyses rely...

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs.

The...