This book explores novel methods for implementing X-ray diffraction technology as an imaging modality, which have been made possible through recent breakthroughs in detector technology, computational power, and data processing algorithms. The ability to perform fast, spatially-resolved X-ray diffraction throughout the volume of a sample opens up entirely new possibilities in areas such as material analysis, cancer diagnosis, and explosive detection, thus offering the potential to revolutionize the fields of medical, security, and industrial imaging and detection. Featuring chapters written by an international selection of authors from both academia and industry, the book provides a comprehensive discussion of the underlying physics, architectures, and applications of X-ray diffraction imaging that is accessible and relevant to neophytes and experts alike.

• Teaches novel methods for X-ray diffraction imaging
• Comprehensive and self-contained discussion of the relevant physics, imaging techniques, system components, and data processing algorithms
• Features state-of-the-art work of international authors from both academia and industry.
• Includes practical applications in the medical, industrial, and security sectors

Joel A. Greenberg received his B.S.E. in Mechanical and Aerospace Engineering from Princeton University in 2005, and his Ph.D. in physics from Duke University in 2012. He then joined the Duke Imaging and Spectroscopy Program in 2012 as a research scientist and technical/project manager of the computational adaptive X-ray imaging (CAXI) program. Since 2014, Joel has been an Assistant Research Professor of Electrical and Computer Engineering at Duke University and a member of the Fitzpatrick Institute for Photonics. He has published over 30 papers in the areas of nonlinear optics, cold atom physics, compressed sensing and X-ray imaging. His current research focuses on computational sensing and its application to security, medical, and industrial imaging and detection.