Yashwant Kurmi

Yashwant
Kurmi
Postdoctoral Research Fellow
(507) 782-9422

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@vumc.org

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.

Kamal
Jouad
Ph.D.
Research Fellow
kamal.jouad@vumc.org

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.

Xia
Li
Ph.D.

Fellow, 2002 thru 2007

Current: Applied Computer Vision Scientist, Amazon Robotics, Boston, MA

Qin Qin, Ph.D.

Qin
Qin
Ph.D.

Graduate Student 2000 thru 2006

Current: Associate Professor of Radiology and Radiological Science, John Hopkins University

Brian Welch, Ph.D.

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.

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.

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

Changzhe
Liu
Graduate Student, Electrical & Computer Engineering
(615) 238-7284

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.

Changzhe.liu@vanderbilt.edu

Saikat Sengupta

Saikat T
Sengupta
Ph.D.

Graduate Student, Postdoctoral Fellow 2005 thru 2015

Current: Research Associate Professor of Radiology and Radiological Sciences, Vanderbilt University Institute of Imaging Science