During the 109th Scientific Assembly and Annual Meeting of RSNA 2023, Fang organized and hosted an educational session titled “Deep Learning in MRI“. The session featured two speakers who spoke about recent research and clinical updates on AI in MRI. Dr. Susie Huang from MGH/HST Martinos Center discussed the use of AI in rapid MRI, […]
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📣I3T Lab Presents Research at Martinos Mesoscale Mapping Symposium
The Center for Mesoscale Mapping at Massachusetts General Hospital and the HST-based Neuroimaging Training Program announces “Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging,” a new symposium bringing together researchers using a range of imaging techniques to study brain function at the intersection of the micro- and macro- scales. I3T lab is pleased to […]
Funding , Highlight
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Lab awarded NIAMS R56 Grant for developing new imaging biomarkers assessing knee osteoarthritis
We are thrilled to receive a 1-year R56 bridge grant from The National Institutes of Health and National Institute of Arthritis and Musculoskeletal and Skin Disease (NIAMS). This new funding will support our lab to develop a multi-parametric imaging method capable of providing rapid, accurate, and efficient non-invasive imaging biomarkers to assess knee joint degeneration in knee osteoarthritis. This […]
Awards , Presentation
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I3T Lab Presents Research at the 2023 ISMRM Annual Meeting
During the 31st ISMRM Annual Meeting in Toronto, Canada, held between June 3-8, 2023, our lab delivered multiple presentations. Dr. Albert Jang presented two papers, namely “Novel 3D Quantitative Magnetization Transfer Imaging of The Whole Knee Cartilage” as an oral presentation and “BTX: Simultaneous 3D Quantitative Magnetization Transfer Imaging And Susceptibility Mapping” as an e-poster […]
Awards , Presentation
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Abert awarded the Best Open Source Tool Award at the 2023 ISMRM Annual Meeting
Dr. Albert Jang, a member of our lab, has received the Best Open Source Tool Award from the ISMRM quantitative MR Study Group. This recognition was given in honor of his participation in the ISMRM 2023 open-source challenge. Our software, MRiLab, was selected as the winning tool by the ISMRM qMR committee due to its […]
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Fang gave an educational talk at the 2022 RSNA
In the 108th Scientific Assembly and Annual Meeting of RSNA 2022, Fang was invited to organize and host an educational session entitled “Deep Learning in MRI.” He also delivered a presentation entitled “Deep Learning Reconstruction for Improving (Accelerating) MRI and MRI-Based Tissue Quantification,” detailing fundamental MRI physics and image formulation and explaining how modern AI […]
Awards
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Wei won the ISMRM Merit Award Magna Cum Laude (15% percentile)
Lab member Wei Peng won the ISMRM Merit Award Magna Cum Laude (15% percentile) in the 30th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM) in London, UK, 2022 for the work entitled “Learning Optimal K-space Acquisition and Reconstruction using Physics-Informed Neural Networks.”
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Lab receives NIAMS R01 Grant for developing new quantitative MRI technology
We are thrilled to receive another 5-year R01 grant from The National Institutes of Health and National Institute of Arthritis and Musculoskeletal and Skin Disease (NIAMS). This new funding will support our lab to develop cutting-edge Artificial Intelligence and Machine Learning methods to improve MRI and image-based non-invasive human tissue quantification, particularly through ultra-high-resolution multi-dimensional quantitative imaging. We aim to explore, implement and optimize a […]
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Congratulation! Lab is awarded NIH R01 Grant for Deep Learning and Rapid Imaging
We are delighted to receive a new 5-year R01 grant from The National Institutes of Health and the National Institute of Arthritis and Musculoskeletal and Skin Disease (NIAMS). This new funding will support our lab at Harvard Medical School and Massachusetts General Hospital to explore a fundamentally new approach to advancing musculoskeletal MRI in all aspects, including rapid image acquisition, reconstruction, advanced image analysis […]
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Lab receives new Trailblazer R21 Award from NIBIB
We are thrilled to receive a new 3-year Trailblazer R21 Grant entitled “Deep Learning Reconstruction for Rapid Multi-Component Relaxometry” from The National Institutes of Health and the National Institute of Biomedical Imaging and Bioengineering (NIBIB). This exciting project will develop novel Artificial Intelligence and Machine Learning methods to improve MRI speed, accuracy, and efficiency in non-invasively imaging human diseases and quantifying human tissue microstructures […]