Professor Ricardo Otazo
New York University School of Medicine
Imaging at the information rate: Sparse sampling & reconstruction
Wednesday, November 2, 2016 10:30 AM
Costa Commons, CESPR 750
Recent developments during the last decade in the field of applied mathematics have started to change the way we think about image acquisition and reconstruction in MRI. The conventional approach of acquiring one k-space sample per image pixel (Nyquist rate) is inefficient and rather wasteful, since the information content is usually much lower than the number of pixels. The introduction of compressed sensing, which attempts to acquire data at the information rate rather than at the Nyquist rate by exploiting image sparsity and incoherent sampling, started a new era in the development of rapid, efficient and information-rich MRI techniques. This talk will discuss recent developments that go beyond increasing imaging speed and provide new information of clinical interest, such as (1) continuous data acquisition with extra-dimensional reconstruction (e.g., 5D cardiac MRI and 5D contrast-enhanced abdominal MRI); (2) low-rank plus sparse (L+S) models for automatic background suppression and learning of motion fields.
Ricardo Otazo (firstname.lastname@example.org) is an Associate Professor of Radiology at New York University School of Medicine. He received his B.Sc. in Electrical Engineering from Universidad Catolica de Asuncion, Paraguay in 2001, and his M.Sc. and Ph.D. in Electrical Engineering from the University of New Mexico in 2005 and 2007 respectively. His research work aims at developing rapid MRI and low-dose CT techniques using advanced mathematical and physical models based on compressed sensing and low-rank matrix completion.
Hosted by Professor Christine Hendon