A New Vision for Transformative
CAI²R combines three innovative areas of imaging research with a unique model for interdepartmental and industrial collaboration. The center aims at rapid translation of developed technology into clinical practice for the improvement of human health.Learn About the Center
• A new paradigm of continuous image acquisition
• Flexible cross-modality image reconstruction
• New York’s first integrated human MR-PET system
• New York’s first 7 Tesla human MR systemEquipment and Facilities
Transforming Cutting-Edge Technology
into Clinical Reality
• Early engagement of clinicians and industry partners
• Clinical and research operations shared space
• 3 core areas of high public-health impact:
cancer, musculoskeletal, and neurologic disease
Meet Our Personnel
• 70+ basic research staff, 30+ clinical collaborators
• Onsite industry partners & frequent collaborative visits
• Ten founding partner clinical departments
• Multidisciplinary research programs
• Bi-directional teaching & learning by clinicians & scientists
• Integrated Graduate Program on Biomedical Imaging
• Hands-on educational offerings in RF engineeringSee the Course Program
›› Bringing People Together to Create New Ways of Seeing ‹‹
Center for Advanced Imaging Innovation and Research
News & Highlights
"Seeing the Invisible"
On Monday, March 30th, Dmitry Novikov will give a talk on breaking through the Magnetic Resonance Imaging (MRI) resolution limits to the tissue microstructure below.
"Seeing the Invisible," a lecture by Dmitry Novikov
On Monday, March 30th, Dmitry Novikov, Assistant Professor at NYU Center for Biomedical Imaging, will give a talk on breaking through the Magnetic Resonance Imaging (MRI) resolution limits to the tissue microstructure below.
MRI allows clinicians to see structures as small as one millimeter, roughly at the resolution of unaided human sight. At this scale, we can distinguish tissues—but not individual cells they’re composed of. “It’s a hard limit,” said Dr. Novikov in an interview, noting that to see such minutiae through MRI in vivo radiologists would have to scan patients with prohibitively strong magnets for extraordinarily long periods. In other words, “you cannot buy your way out of the limit”—but you may be able to think your way out.
In his lecture, titled Seeing the invisible: Tissue structure at the cellular lever with MRI, Dr. Novikov will talk about using MRI to glimpse microstructures one thousand times smaller than one millimeter. “That’s where physiology happens, that’s where pathology develops,” he noted. This relatively new and still emerging way of seeing depends on taking MRI measurements with conventional millimeter-scale resolution, and developing theoretical models to interpret the resulting data in terms of changes occurring at the scale of microns.
Dr. Novikov’s lecture is a part of the Translational Research In Progress (TRIP) Seminar series hosted by the Clinical and Translational Science Institute, an interdisciplinary partnership among New York University, the NYU Langone Medical Center, and the New York City Health and Hospitals Corporation.
Details: Monday, March 30th, 1:00pm, Smilow Research Center (map), 1st Floor Multipurpose Room.
In a paper published recently in NMR in Biomedicine, Florian Knoll describes a new way to reconstruct parametric maps from scan data in diffusion MRI.Read more
SPIE 2015 Lecture
During this year’s SPIE Medical Imaging conference, CAI²R's Dan Sodickson gave a plenary lecture on "The Rapid Imaging Renaissance", which is now available online.Read more
Researchers at NYU’s Center for Advanced Imaging Innovation Research have developed a new way to measure changes in microstructure of muscle fiber.Read more
Diffusion Imaging of Cartilage Makes JMRI Cover
The journal JMRI highlights Jose Raya's work on diffusion tensor imaging assessments of articular cartilage.
Diffusion Imaging to Assess Cartilage Makes JMRI Cover
In the June issue of the Journal of Magnetic Resonance Imaging, Dr. Raya, who develops methods for early detection of osteoarthritis, describes diffusion tensor imaging (DTI) techniques for assessment of cartilage composition and structure. In particular, he employs two DTI measures—mean diffusivity and fractional anisotropy—to evaluate two fundamental elements of cartilage tissue—proteoglycan and collagen.
The images on the cover of JMRI show longitudinal changes in DTI measurements of the knee in two patients diagnosed with osteoarthritis. The data indicate that proteoglycan content may decrease even as the structure of collagen fibers remains relatively stable. The results also demonstrate that diffusion parameters can characterize physiological changes occurring over time. Read about this and related techniques in Dr. Raya’s paper, Techniques and application of in vivo diffusion imaging of articular cartilage.
MRI for Next Generation Smartphones
NYU researchers advocate new wireless safety standards, with MRI playing key role.Read more
NYU at ISMRM 2015
CAI2R scientists presented latest research and shared expertise at the 23rd annual meeting of the International Society for Magnetic Resonance in Medicine.Read more
Fernando Boada Named Distinguished Investigator
The Academy of Radiology Research, has named CAI2R director Fernando Boada a Distinguished Investigator.
An advocacy based in Washington, D.C., the Academy of Radiology Research champions recognition of the role of imaging research in medical practice, and advocates dedicated funding for imaging technologies that profoundly influence healthcare.
This year the academy has honored Dr. Fernando Boada alongside 36 researchers “for their accomplishments in imaging research” and to “especially encourage those who have achieved scientific excellence while still being involved in clinical care,” according to a congratulatory letter from the Distinguished Investigator Council.
As principal investigator, Dr. Boada leads a technology research and development (TR&D) project to develop convergent MR-PET acquisition and reconstruction methods that go beyond the conventional superposition of MR and PET data.