Daniel Sodickson plenary talk: The Rapid Imaging Renaissance: Sparser Samples, Denser Dimensions, and Glimmerings of a Grand Unified Tomography

The fundamental concepts of tomographic imaging have remained relatively constant since the onset of CT and MRI in the 1970s. However, rapid advances in applied mathematics in the form of compressed sensing techniques over the past decade have provided new ways for the imaging community to collect and reconstruct data.

GRASP (golden angle radial sparse parallel MRI), developed by Daniel Sodickson and his collaborators, has been used on over 3,000 patients, but the method does show residual motion-related artifacts. This led the team to improve the technique by examining motion sorting schemes as opposed to motion correction methods. XD-GRASP (where 'XD' means 'extra dimension') enables multiple images through motion using the same data but sorting the data differently.

Beginning with examples from MRI, then proceeding through selected other modalities such as CT and PET, as well as multimodality combinations, this talk explores the potential of newly evolving acquisition and reconstruction paradigms to change the way imaging is done in the lab and in the clinic.

Daniel K. Sodickson is Vice-Chair for Research in the Department of Radiology and Professor of Radiology, Physiology and Neuroscience at New York University School of Medicine. Dr. Sodickson received a BS in Physics and a BA in Humanities from Yale College. He earned his PhD in Medical Physics from MIT and his MD from Harvard Medical School, both as a part of the Harvard-MIT Division of Health Sciences and Technology.