Shuyang Chai
Miniature and flexible Bazooka balun for high-field MRI
https://www.sciencedirect.com/science/article/abs/pii/S1090780723002124
Low‐cost inductively coupled stacked wireless RF coil for MRI at 3 T
https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/abs/10.10…
My area is about the rf coil system of the MRI
Flexible 7T receive coil
Brain and spinal coil
Yashwant Kurmi
Viswanathan M, Kurmi Y, Zu Z. A rapid method for phosphocreatine-weighted imaging in muscle using double saturation power-chemical exchange saturation transfer. NMR in Biomedicine. 2023;e5089. doi:10.1002/nbm.5089
Viswanathan M, Yin L, Kurmi Y, Zu Z. Machine learning-based amide proton transfer imaging using partially synthetic training data. Magn Reson Med. 2023 Dec 14. doi: 10.1002/mrm.29970. Epub ahead of print. PMID: 38098340.
Viswanathan M, Yin L, Kurmi Y, Zu Z. Amide Proton Transfer (APT) imaging in tumor with a machine learning approach using partially synthetic data. ArXiv [Preprint]. 2023 Dec 13:arXiv:2311.01683v2. Update in: Magn Reson Med. 2023 Dec 14;: PMID: 37961738; PMCID: PMC10635304.
Kurmi Y, Chaurasia V, Ganesh N. Tumor Malignancy Detection Using Histopathology Imaging. J Med Imaging Radiat Sci. 2019 Dec;50(4):514-528. doi: 10.1016/j.jmir.2019.07.004. Epub 2019 Sep 6. PMID: 31501064.
Kurmi, Y. and Chaurasia, V. (2020), Classification of magnetic resonance images for brain tumour detection. IET Image Process., 14: 2808-2818. https://doi.org/10.1049/iet-ipr.2019.1631
Yashwant Kurmi is a researcher with expertise in image processing and machine learning, particularly in the areas of deep learning and chemical exchange saturation transfer (CEST) imaging. He has authored several papers on MRI imaging, including amide proton transfer (APT) imaging in tumors using a machine learning approach, and quantitative CEST molecular MR imaging.
Deep learning based CEST MR image enhancement and the quantification.
Kamal Jouad, Ph.D.
Development of radiopharmaceuticals and opticals agent for preclinical and clinical research.
My research project aims to fully automated manufacturing of imaging probes for precision surgery utilizing cancer-targeted moieties (antibodies, affibodies, small molecules, etc.) conjugated to radioisotopes (89Zr, 111In, 18F, 68Ga, etc.) or optical fluorescent dye (IRDye800, ICG)
Xia Li, Ph.D.
Fellow, 2002 thru 2007
Current: Applied Computer Vision Scientist, Amazon Robotics, Boston, MA
Qin Qin, Ph.D.
Graduate Student 2000 thru 2006
Current: Associate Professor of Radiology and Radiological Science, John Hopkins University
Brian Welch, Ph.D.
Assistant Professor, Scientific Manager, Human Imaging Core 2010 thru 2017
Current: Vice President of Clinical Partnerships at InkSpace Imaging
Eugene Lin, Ph.D.
Postdoc Fellow 2015 thru 2018
Current: Assistant Professor, Department of Chemistry and Biochemistry, National Chung Cheng University, Taiwan
Xiawei Ou, Ph.D.
Research Fellow 2003 thru 2007
Current: Professor of Radiology & Pediatrics and MR Physicist, University of Arkansas for Medical Sciences, Little Rock, AK
Changzhe Liu
Developing a Novel B0 Shimming Method and a Wireless Implantable Coil for MRI.
In our project, we enhance MRI quality by advancing "RF transparent" DC coil technology, a leap forward in reducing B0 inhomogeneity. Diverging from traditional methods, our approach minimizes the use of bulky RF chokes by employing separate local DC coils, thus allowing greater design freedom and easier implementation of multiple turns. A significant challenge - the strong coupling between DC and RF coils - is addressed by our novel "RF transparent" DC coil. This innovation has minimal impact on RF performance, effectively solving the coupling issue while optimizing imaging quality. Our work not only paves the way for more precise MRI imaging but also showcases a scalable solution that can be integrated into existing MRI systems.