Radiology
Showing 501-550 of 667 Results
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Veit Sandfort
Clinical Assistant Professor, Radiology
BioRadiologist and Cardiologist (Germany) with cardiovascular imaging research/clinical experience. I have a continued interest in clinical cardiovascular imaging and in medical applications of deep learning.
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Amir H. Sarrami
Clinical Assistant Professor, Radiology - Pediatric Radiology
Current Research and Scholarly InterestsPediatric thoracic imaging
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George Segall
Professor of Radiology, Emeritus
Current Research and Scholarly InterestsScintigraphic evaluation of coronary blood flow and myocardial function using single photon emission computed tomography (SPECT) and positron emission tomography (PET). Tumor imaging and characterization of pulmonary nodules with PET/CT.
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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. -
Zahra Shokri Varniab
Postdoctoral Scholar, Radiology
BioZahra Shokri Varniab, MD, studied medicine at Tehran University of Medicine Sciences, Iran, and earned her medical degree in 2021. Her goal in novel cellular and molecular imaging is to develop novel in vivo imaging approaches to visualize, characterize and quantify molecular and cellular processes involved in developing brain tumors. She intends to utilize non-invasive imaging techniques to assess tumor microenvironment to understand their role in cancer, develop a method for determining tumor profiles, and also using brain MR Imaging to assess treatment response. She hopes cancer to be history.
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Pratham Preet Singh
Graduate, Medicine, Radiology
BioPh.D. Kinesiology
University of Toronto – Toronto, ON
Sept 2021 – Aug 2026 (Expected)
M.Sc. Biomedical Engineering (Specialization in Wearable Technology)
University of Calgary – Calgary, AB
Jan 2019 – Jan 2021
B.Eng. With Distinction, Biomedical Engineering (Co-op); B.A., Business Administration
University of Guelph – Guelph, ON
Sept 2012 – Dec 2017 -
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. -
Hyongsok Tom Soh
W. M. Keck Foundation Professor of Electrical Engineering, Professor of Radiology (Diagnostic Sciences Laboratory) and of Bioengineering
BioDr. Soh received his B.S. with a double major in Mechanical Engineering and Materials Science with Distinction from Cornell University and his Ph.D. in Electrical Engineering from Stanford University. From 1999 to 2003, Dr. Soh served as the technical manager of MEMS Device Research Group at Bell Laboratories and Agere Systems. He was a faculty member at UCSB before joining Stanford in 2015. His current research interests are in analytical biotechnology, especially in high-throughput screening, directed evolution, and integrated biosensors.
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Hong Song, MD, PhD
Assistant Professor of Radiology (Nuclear Medicine)
BioHong Song received his MD from Tulane University School of Medicine and a Ph.D. in Chemical Engineering from Tulane University. He performed research in targeted radionuclide therapy as a postdoctoral fellow at the Johns Hopkins University. Following medical school, he joined Dual pathway Nuclear Medicine and Diagnostic Radiology residency at Stanford. His current research interests include PSMA PET in biochemically recurrent prostate cancer and DOTATATE PET in PRRT for neuroendocrine tumors.
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Geoffrey Sonn
Associate Professor of Urology and, by courtesy, of Radiology (Body MRI)
Current Research and Scholarly InterestsMy interest is in improving prostate cancer diagnosis through MRI and image-targeted prostate biopsy. In collaboration with radiologists at Stanford, we are working to define the optimal role of MRI in prostate cancer. We hope to improve cancer imaging to the point that some men with elevated PSA may safely avoid prostate biopsy. For those who need biopsy, we are evaluating novel MRI-US fusion targeted biopsy, a technique that greatly improves upon the conventional biopsy method.
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Daniel Spielman
Professor of Radiology (Radiological Sciences Lab) and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsMy research interests are in the field of medical imaging, particularly magnetic resonance imaging and in vivo spectroscopy. Current projects include MRI and MRS at high magnetic fields and metabolic imaging using hyperpolarized 13C-labeled MRS.
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Kate Stevens
Professor of Radiology (Musculoskeletal Imaging)
Current Research and Scholarly InterestsSports medicine - imaging of sports injuries in athletes and ultrasound-guided therapy.
Clinical applications of new MRI pulse sequences.
Metal suppression MRI around orthopedic implants.
Imaging and guided therapy in rheumatology. -
Liyan Sun
Postdoctoral Scholar, Radiological Sciences Laboratory
Current Research and Scholarly InterestsPhysics-driven deep learning algorithms for MRI/CT reconstruction and analysis:
(1) MRI acceleration with partial measurements.
(2) Medical image segmentation under limited data resources.
(3) Unsupervised/supervised medical image synthesis for MRI or CT.
(4) Longitudinal medical data analysis with deep learning models.
(5) PET image reconstruction and analysis.
