Center for Advanced Imaging Innovation and Research (CAI2R) at NYU Langone Health

Earlier this fall, the National Institutes of Health awarded $6.7 million to NYU Grossman School of Medicine to continue operating our Center for Advanced Imaging Innovation and Research (CAI2R) for another five-year term. The award extends our status as a National Center for Biomedical Imaging and Bioengineering and marks the tenth anniversary of our center's founding. "We are at a truly remarkable juncture in the history of imaging," said Dan Sodickson, CAI2R founding principal investigator, as he reflected on the center's greatest accomplishments and outlined its goals for the coming years. In this blog post, we celebrate the milestone anniversary and look at what's next: https://lnkd.in/ehZaxmmV Biomedical imaging research is an intensely collaborative endeavor, and we are grateful for all the resources and talent that enable our work. In particular, we acknowledge and thank the National Institute of Biomedical Imaging and Bioengineering (NIBIB) for its continued support; NYU Langone Health and its radiology department for their unwavering commitment to our team; and all of our many research partners and colleagues for their myriad contributions to our mission of improving health through imaging. We are so excited to continue to envision, discover, develop, and build the future of this fascinating field. CC: Li Feng, Ryan Brown, Christopher Collins, Els Fieremans, Dmitry Novikov, Riccardo Lattanzi, Hersh Chandarana #radiology #research #innovation in #MRI and #biomedicalimaging #science #engineering #medicine #health #ScienceWithoutBorders

Wednesday, November 20, at noon, as part of our radiology research forum: "Genetic Control of MRI Contrast Using the Manganese Transporter Zip14," with Harikrishna Rallapalli, PhD, postdoctoral fellow at the National Institute of Neurological Disorders and Stroke (NINDS), The National Institutes of Health. Talk details: https://lnkd.in/egHFgkVv #radiology #research #MRI in #genetics #genomics #GeneExpression #proteomics

Wednesday, November 13, at noon, as part of our radiology research forum: "Image-Derived Disease Biomarkers in Breast Cancer and Lung Disease," with Gabrielle Baxter, PhD, who recently completed postdoctoral training at UCL. Talk details: https://lnkd.in/e46NTvCq #radiology #research #MRI in #BreastCancer and #LungDisease

🎓🎓🎓 Applications to our PhD program in biomedical imaging & technology at NYU Grossman School of Medicine are open. Join us for an info session to learn more! Thursday, November 14, at 10:00 am ET via Zoom Register: https://lnkd.in/e_7A_tUv Hosts and panelists: Riccardo Lattanzi, PhD, program director Steven Baete, PhD, graduate advisor Dmitry Novikov, PhD, mentoring faculty member Carlotta Ianniello, PhD, alumna Radhika Tibrewala, PhD, alumna 🙋🏾♀️🙋🏻🙋🏻♀️🙋🏽♂️ Students in the PhD program work closely with scientists at our imaging research center at NYU Langone Health, making significant contributions to imaging technologies and their applications in basic and clinical research. For example: 🌟 Radhika Tibrewala, PhD, alumna ('24), co-created the first dataset of annotated raw diffusion MRI data for machine learning research: https://lnkd.in/eEKpj4E8 🌟 Carlotta Ianniello, alumna ('21), conducted research that enabled later investigations into sodium MRI for evaluation of breast cancer response to chemotherapy: https://lnkd.in/e7PYEJRg 🌟 Ruoxun Zi, current doctoral candidate in our program, is on a research team deciphering the kinematics of the wrist: https://lnkd.in/dJ3BKXyb 🌟 Jungkyu (JP) Park, current doctoral candidate, worked with a team of clinicians and scientists to create a winning machine learning algorithm for detecting cancer in digital breast tomosynthesis data: https://lnkd.in/eSrdzKUK 🌟 Hong-Hsi Lee, alumnus ('19), and faculty mentors conducted research showing that MRI is sensitive to variations in the diameters of axons: https://lnkd.in/eshetEeK 🌟 Anna Chen, current doctoral candidate, is the lead author on an investigation into reproducibility of magnetic resonance spectroscopy applications in traumatic brain injury: https://lnkd.in/eiHNy9JN What would you want to work on in your PhD research? Join us at an info session and let us know! More about the biomedical imaging and technology PhD training program at NYU Grossman: https://lnkd.in/e53SS-95 #PhD #PhDlife #STEM #research #science #engineering #medicine #admissions

Wednesday, October 30, at noon, as part of our radiology research forum: "Diffusion MRI of the Hippocampus: Why Care, What We Know, and What We Hope to Know," with Bradley Karat, doctoral candidate in neuroscience at Western University. Talk details: https://lnkd.in/et8qHwJG #radiology #research #diffusion #MRI #neuroimaging and #neuroscience

I really enjoyed the ISMRM MRS workshop in Boston last week. Engaging talks and great company! There was a wonderful surprise too: seeing our lab’s graduate student Anna Chen receiving the award for the best clinical application abstract! A proud moment for the lab and our center! Congrats, Anna! Anna Chen Center for Advanced Imaging Innovation and Research (CAI2R) at NYU Langone Health NYU Grossman School of Medicine ISMRM

On Monday, our Center for Biomedical Imaging at NYU Langone Health held a "science day," a daylong gathering with scientific talks, imaging-themed games, panel discussions, poster presentations, and lots of interaction throughout—organized for us and by us to celebrate community and collaboration in our growing team. (We held our first science day last year and liked it so much that right away we knew it wouldn't be our last.) Taking a day to survey our work, share professional experience, exchange perspectives, and connect across the range of research interests helps us better tap into our best and most valuable resource: each other. CC: NYU Grossman School of Medicine #radiology #research #innovation in #science and #medicine #interdisciplinary #collaboration #TeamSpirit #ScienceWithoutBorders

🎓🎓🎓 Applications to our PhD program in biomedical imaging & technology at NYU Grossman School of Medicine are open. Join us for an info session to learn more! Thursday, November 14, at 10:00 am ET via Zoom Register: https://lnkd.in/e_7A_tUv Hosts and panelists: Riccardo Lattanzi, PhD, program director Steven Baete, PhD, graduate advisor Dmitry Novikov, PhD, mentoring faculty member Carlotta Ianniello, PhD, alumna Radhika Tibrewala, PhD, alumna 🙋🏾♀️🙋🏻🙋🏻♀️🙋🏽♂️ Students in the PhD program work closely with scientists at our imaging research center at NYU Langone Health, making significant contributions to imaging technologies and their applications in basic and clinical research. For example: 🌟 Radhika Tibrewala, PhD, alumna ('24), co-created the first dataset of annotated raw diffusion MRI data for machine learning research: https://lnkd.in/eEKpj4E8 🌟 Carlotta Ianniello, alumna ('21), conducted research that enabled later investigations into sodium MRI for evaluation of breast cancer response to chemotherapy: https://lnkd.in/e7PYEJRg 🌟 Ruoxun Zi, current doctoral candidate in our program, is on a research team deciphering the kinematics of the wrist: https://lnkd.in/dJ3BKXyb 🌟 Jungkyu (JP) Park, current doctoral candidate, worked with a team of clinicians and scientists to create a winning machine learning algorithm for detecting cancer in digital breast tomosynthesis data: https://lnkd.in/eSrdzKUK 🌟 Hong-Hsi Lee, alumnus ('19), and faculty mentors conducted research showing that MRI is sensitive to variations in the diameters of axons: https://lnkd.in/eshetEeK 🌟 Anna Chen, current doctoral candidate, is the lead author on an investigation into reproducibility of magnetic resonance spectroscopy applications in traumatic brain injury: https://lnkd.in/eiHNy9JN What would you want to work on in your PhD research? Join us at an info session and let us know! More about the biomedical imaging and technology PhD training program at NYU Grossman: https://lnkd.in/e53SS-95 #PhD #PhDlife #STEM #research #science #engineering #medicine #admissions

On Wednesday we made available a new deep learning model for research on magnetic resonance electrical properties tomography. We're now pleased to add that our peer-reviewed report about this model has been published in the journal Magnetic Resonance in Medicine, where the research team calls the advance "an important step towards the development of clinically-usable in vivo [electrical properties] reconstruction protocols." 📄 The paper: https://lnkd.in/dE6kJHbC 👇 More info and links to the resource, below.

📦 We are sharing a new resource for imaging researchers investigating magnetic resonance electrical properties tomography: a 3D vision transformer-based neural network for fast and accurate reconstruction of electrical properties from MRI data. Magnetic resonance electrical properties tomography (MR-EPT) is used to estimate electric conductivity and relative permittivity in tissues based on MRI data. This kind of analysis provides valuable information about interactions between electromagnetic waves and biological tissues, and has the potential to enable many promising applications in biomedical research and medicine. However, MR-EPT is computationally challenging and traditional methods tend to be slow and imprecise. We are now making available a deep learning model that outperforms traditional methods. For more information, visit https://lnkd.in/e4rpqUeU 🏅 Ilias Giannakopoulos, postdoctoral fellow with our research center at NYU Langone Health and lead author of this research, was honored for this advance at the 2024 meeting of the International Society for Magnetic Resonance in Medicine (ISMRM) in Singapore with a magna cum laude award and recently presented at the 2024 joint workshop on MR phase, magnetic susceptibility and electrical properties mapping in Chile (EMTP Chile) in a session dedicated to the state of the art in EPT. A peer-reviewed publication describing this advance, its validation, and the team's findings is forthcoming. CC: Giuseppe Carluccio, Gregor Körzdörfer, karthik lakshmanan, Hector Lise de Moura, José E. Cruz Serrallés, Ph.D., Zheng Zhang, Xinling Y., Bruno Mary, Riccardo Lattanzi #MachineLearning and #DeepLearning in #MRI #ComputerScience #ElectricalEngineering #Physics & #Mathematics in #biomedicalimaging #AI & ##ML in #radiology #research #OpenScience #ScienceWithoutBorders