Radiology
Showing 21-40 of 58 Results
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Kawin Setsompop
Professor of Radiology (Radiological Sciences Laboratory) and, by courtesy, of Electrical Engineering
BioKawin Setsompop is a Professor of Radiology and, by courtesy, of Electrical Engineering. His research focuses on the development of novel MRI acquisition methods, with the goal of creating imaging technologies that can be used to help better understand brain structure and function for applications in Healthcare and Health sciences. He received his Master’s degree in Engineering Science from Oxford University and his PhD in Electrical Engineering and Computer Science from MIT. Prior to joining Stanford, he was a postdoctoral fellow and subsequently a faculty at the A.A. Martinos center for biomedical imaging, MGH, as well as part of the Harvard and MIT faculty. His group has pioneered several widely-used MRI acquisition technologies, a number of which have been successfully translated into FDA-approved clinical products on Siemens, GE, Phillips, United Imaging and Bruker MRI scanners worldwide. These technologies are being used daily to study the brain in both clinical and neuroscientific fields.
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Shailja
Postdoctoral Scholar, Radiological Sciences Laboratory
BioShailja is an engineer and computational scientist interested in the modeling of the human brain to study neurological diseases and guide neurosurgeries. As a Wu Tsai Neuroscience Institute’s postdoctoral fellow with Prof. Jennifer A. McNab and Prof. Josef Parvizi, she investigates tractography-based neurosurgical targeting. She is interested in mapping the whole brain structural connectivity network from diffusion MRI to functional connectivity in the human brain. Shailja received her PhD in Electrical and Computer Engineering from the University of California, Santa Barbara and BS from Electrical Engineering Department, Indian Institute of Technology, Kharagpur. Her doctoral research is on Reeb graphs for modeling white matter fibers in the human brain, which was awarded the Winifred and Louis Lancaster Best PhD Dissertation at UC Santa Barbara.
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Richard Shan
Affiliate, Rad/Integrative Biomedical Imaging Informatics at Stanford
BioRichard Shan is an AI researcher focused on mechanistic interpretability and retrieval-augmented generation. His work centers on building pipelines to evaluate and optimize reasoning in large language models, including novel architectures for feature identification and correctness evaluation. He develops applied systems that combine AI with linguistics, such as a modular refreshable Braille device and computational methods for reconstructing ancient languages. Outside of technical work, Richard enjoys playing frisbee.
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Luyao Shen, MD
Clinical Associate Professor, Radiology
Current Research and Scholarly InterestsGU and Gyn clinical imaging
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Vipul Sheth, MD, PhD
Assistant Professor of Radiology (Body MRI)
Current Research and Scholarly InterestsMy interests are in the development and translation of imaging technologies geared toward disease detection and characterization to better guide prognosis, treatment, and improve outcomes. I’m interested in supporting the development of MRI guided focal therapy methods which can personalize treatment and reduce the risk of morbidity from more invasive therapies.
Clinical Interests
- MRI for diagnosis of pelvic floor disorders
- MRI and PET/MRI to pelvic malignancies and lymph node staging.
- Whole Body MRI
- MRI guided procedures including biopsies, cryoablation, and high intensity focused ultrasound.
Translational Research Interests
- Development and translation of magnetic resonance imaging technologies to improve both diagnostics and therapeutics
- Molecular imaging and characterization of the tumor microenvironment
- Ultrashort echo time MRI applications in the body
- Developing synergistic MRI methods to complement PET in potential applications for PET/MRI -
Linxi Shi
Sr Res Scientist-Physical, Rad/Radiological Sciences Laboratory
BioI am a medical physicist and imaging scientist with over a decade of experience in CT imaging, algorithm development, and AI-driven reconstruction. I earned my Ph.D. in Medical Physics from the Georgia Institute of Technology, where I developed novel artifact corrections and reconstruction algorithms for cone beam computed tomography, focusing on applications in breast cancer diagnosis and image-guided radiation therapy.
Following my doctoral studies, I completed a postdoctoral fellowship with the Stanford Cancer Imaging Training (SCIT) Program. Currently, I serves as a Senior Research Scientist in the Radiological Sciences Laboratory at Stanford University. My research focuses on developing advanced clinical translational x-ray and CT imaging systems, including algorithm design for tomographic reconstruction, artifact correction, and image processing for various imaging modalities. -
Bruno Passebon Soares, MD
Associate Professor of Radiology (Pediatric)
BioDr. Soares is an Associate Professor of Radiology at Stanford University School of Medicine and serves as the Section Chief of Pediatric Neuroradiology at Lucile Packard Children’s Hospital at Stanford since June 2023.
Born in Brazil, Dr. Bruno P. Soares obtained his medical degree from the Federal University of Rio de Janeiro and completed his residency in Diagnostic Radiology at the Federal University of Sao Paulo. After one year as a Research Fellow at the University of California San Francisco (UCSF), Dr. Soares completed clinical fellowships in Diagnostic Neuroradiology, Pediatric Radiology, and Pediatric Neuroradiology at UCSF, in addition to a clinical fellowship in PET/CT at the Dana-Farber Cancer Institute of Harvard Medical School in Boston. Dr. Soares holds a subspecialty certificate in Neuroradiology from the American Board of Radiology (ABR).
From July 2013 to July 2016, Dr. Soares was an Assistant Professor in the Division of Neuroradiology at Emory University in Atlanta. From August 2016 to November 2018, he worked at the Johns Hopkins University in Baltimore as an Assistant Professor in the Division of Pediatric Radiology and Neuroradiology. From December 2018 to May 2023, Dr. Soares worked at the University of Vermont Medical Center as Associate Professor of Radiology, Division Chief of Neuroradiology, Vice-Chair of Imaging Research, and Co-Director of the MRI Center for Biomedical Imaging.
Dr. Soares has published more than 85 peer-reviewed articles and has been the recipient of the Research Fellow Grant from the Society for Pediatric Radiology and of the Rad_Britestar Award from the Johns Hopkins Department of Radiology. The recognition for his teaching includes the 2013 Outstanding Clinical Fellow / Instructor Teaching Award from the UCSF Department of Radiology, the 2017 Teacher of Year Award from the Johns Hopkins Division of Pediatric Radiology, and the 2017 ASNR International Outreach Professor Program in Ghana.
Dr. Soares currently serves as an Editorial Board Member of Neuroradiology and of the Journal of Neuroimaging, and has served as an Editorial Board Member of the American Journal of Roentgenology (AJR) and of the American Journal of Neuroradiology (AJNR). Dr. Soares served for six years as a member of the ABR Neuroradiology Core Exam Committee, receiving ABR Volunteer Service Awards in 2022 and 2024.
His research has focused on neonatal and pediatric brain imaging. He is currently focused on developing semi-automated algorithms to quantify normal and abnormal brain development, and applying deep learning algorithms for detection of subtle cerebral abnormalities in children with epilepsy.
