Radiology
Showing 101-200 of 688 Results
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Meysam Dadgar
Postdoctoral Scholar, Molecular Imaging Program at Stanford
BioMeysam Dadgar is a Postdoctoral Research Fellow at the Molecular Imaging Program at Stanford University, School of Medicine. He obtained his Ph.D. in Biophysics from Jagiellonian University in Kraków, Poland, as part of the J-PET collaboration, and previously held a Postdoctoral Fellowship at Ghent University, Belgium.
Dr. Dadgar’s research focuses on the development and optimization of next-generation positron emission tomography (PET) systems for cancer detection and precision medicine. His expertise spans PET instrumentation, Monte Carlo and GATE simulations, advanced image reconstruction, and AI-based image enhancement. He has made significant contributions to the design and evaluation of novel PET geometries, including dual-panel and total-body PET, as well as positronium imaging approaches that extend beyond conventional PET capabilities.
In addition to his PET-focused research, Dr. Dadgar gained unique experience at CERN, where he worked on advanced detector development, including trigger electronics, PET coincidence measurements, and composite material production under controlled conditions. These experiences provided him with a strong foundation in detector design, fabrication, and calibration that complements his biomedical imaging research.
He has authored more than 20 peer-reviewed publications, including papers in Science Advances, Nature Communications, IEEE Transactions on Radiation and Plasma Medical Sciences, and EJNMMI Physics. He has been recognized with multiple international fellowships and awards, including IEEE NSS/MIC Trainee Grants and national research grants in Europe.
At Stanford, Dr. Dadgar’s work integrates state-of-the-art medical imaging technologies, particle physics methods, and AI-driven modeling to improve sensitivity, resolution, and diagnostic accuracy in PET, with the ultimate goal of advancing early cancer detection and patient care. -
Jeremy Dahl
Professor of Radiology (Pediatric Radiology)
Current Research and Scholarly InterestsMy current research encompasses ultrasonic beamforming and image reconstruction methods, with application areas in improving ultrasound image quality in difficult-to-image patients and ultrasound molecular imaging of cancer. My lab also employs beamforming concepts to enhance other areas of ultrasound research.
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Heike Daldrup-Link
Professor of Radiology (General Radiology) and, by courtesy, of Pediatrics (Hematology/Oncology)
Current Research and Scholarly InterestsAs a physician-scientist involved in the care of pediatric patients and developing novel pediatric molecular imaging technologies, my goal is to link the fields of nanotechnology and medical imaging towards more efficient diagnoses and image-guided therapies. Our research team develops novel imaging techniques for improved cancer diagnosis, for image-guided-drug delivery and for in vivo monitoring of cell therapies in children and young adults.
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Roxana Daneshjou, MD, PhD
Assistant Professor of Biomedical Data Science and of Dermatology and, by courtesy, of Radiology
BioDr. Daneshjou studied Bioengineering at Rice University before matriculating to Stanford School of Medicine where she completed her MD and a PhD in Genetics with Dr. Russ Altman as part of the medical scientist training program. She completed dermatology residency at Stanford as part of the research track and completed a postdoc in Biomedical Data Science with Dr. James Zou. She currently is the assistant director of the Center of Excellence for Precision Heath & Pharmacogenomics, director of informatics for the Stanford Skin Innovation and Interventional Research Group (SIIRG), a founding member of the Translational AI in Dermatology (TRAIND) group, and a faculty affiliate of Human-centered Artificial Intelligence (HAI) and the AI in Medicine and Imaging (AIMI) centers.
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Bruce Daniel
Professor of Radiology (Body Imaging) and, by courtesy, of Bioengineering
Current Research and Scholarly Interests1. MRI of Breast Cancer, particularly new techniques. Currently being explored are techniques including ultra high spatial resolution MRI and contrast-agent-free detection of breast tumors.
2. MRI-guided interventions, especially MRI-compatible remote manipulation and haptics
3. Medical Mixed Reality. Currently being explored are methods of fusing patients and their images to potentially improve breast conserving surgery, and other conditions. -
Guido A. Davidzon
Clinical Professor, Radiology - Rad/Nuclear Medicine
BioDr. Guido Alejandro Davidzon is a Clinical Professor of Radiology in Nuclear Medicine at the Stanford University School of Medicine. He currently serves as Director of Nuclear Cardiology at Stanford Health Care and is the Chair of the Radioactive Drug Research Committee.
Dr. Davidzon is a physician-scientist, educator, and leader whose work bridges clinical innovation, academic leadership, and translational research. His research focuses on the development and clinical translation of novel radiopharmaceuticals for use in oncology, neurodegeneration, cardiology, and pain imaging. He is also actively integrating AI-driven analytics and machine learning tools into molecular imaging to advance precision diagnostics and therapeutic decision-making.
His clinical and academic efforts include advancing theranostics, PET-based biomarker discovery, and the adoption of emerging imaging technologies in patient care. Dr. Davidzon is deeply committed to mentorship and the training of the next generation of imaging specialists and nuclear medicine professionals. -
Braden Michael Dawson
Affiliate, Radiology
BioBraden Dawson is an undergraduate student at the University of Southern California studying Legal Studies and Natural Science on pre-medical and pre-law tracks. His work focuses on health policy, healthcare systems, and translational medicine, with interests in healthcare access, implementation, and regulatory design. At Stanford School of Medicine, he is a Canary CREST Research Intern, conducting translational cancer early-detection research under Parag Mallick, PhD.
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Johannes Hugo Decker
Clinical Assistant Professor, Radiology
BioHugo Decker is part of the Diagnostic Radiology resident call of 2018-2022.
He received his BS in Biological Sciences at Stanford in 2008.
He completed his MSTP training at Weill Cornell Medical College in 2017.
He completed his Medical internship at Santa Clara Valley Medical Center in 2018. -
Wendy DeMartini
Professor of Radiology (Breast Imaging)
BioDr. Wendy DeMartini is a Professor in the Department of Radiology at Stanford University School of Medicine. She currently serves as the Associate Chair for Clinical Faculty Affairs in the Department of Radiology, and is the past Division Chief of Breast Imaging. Her work is focused upon high quality patient care, clinical research and education.
Dr. DeMartini completed her fellowship in Breast Imaging at the University of Washington School of Medicine in Seattle, Washington. She then served as Breast Imaging faculty at the University of Washington where she became Associate Professor and Associate Director of Clinical Services, and at the University of Wisconsin where she became Professor and Chief of Breast Imaging.
Dr. DeMartini has more than 100 research presentations, abstracts/publications, review articles or book chapters. Her research is directed toward the appropriate evidence-based use of imaging tests to optimize the detection and evaluation of breast cancer. She has served as an investigator on several studies of breast MRI funded by the National Cancer Institute and by the American College of Radiology Imaging Network (ACRIN). Particular research topics have included the development of a pilot tool for predicting the probability of malignancy of breast MRI lesions, assessment of the impact of background parenchymal enhancement (BPE) on breast MRI accuracy, and evaluation of utilization patterns of breast MRI and other emerging technologies. She also served as the Editor-in-Chief of the Journal of Breast Imaging from 2023 to 2024.
Dr. DeMartini is a highly sought-after educator. She lectures on a broad spectrum of breast imaging topics nationally and internationally, including in the Americas, Europe, Australasia and Africa. She is the past Co-Director of the American College of Radiology (ACR) Education Center Breast MRI with Biopsy Course. Dr. DeMartini is an active member of many professional organizations and committees, including in the Radiologic Society of North America, the American College of Radiology and the Society of Breast Imaging (SBI). She was elected as an SBI Fellow in 2009 and served as President of the SBI in 2017-2018. -
Utkan Demirci
Professor of Radiology (Diagnostic Sciences Laboratory) and, by courtesy, of Electrical Engineering
BioDr. Utkan Demirci, UofM’99, Stanford’01’05’05, is a Professor of Radiology (with tenure) and of Electrical Engineering (by courtesy) at the Canary Center at Stanford for Cancer Early Detection, Stanford University School of Medicine, where he leads a productive researcher group. Utkan is a tenured professor at Stanford University School of Medicine. Prior to joining Stanford in 2014, he held the position of Associate Professor at the Brigham and Women’s Hospital-Harvard Medical School and also served at the Harvard-MIT Health Sciences and Technology division. Over the past decade, his research group has focused on the early detection of cancer and has made significant contributions to the development of microfluidic platforms for sorting rare cells and exosomes and point-of-care bio-sensing technologies.
Dr. Demirci leads a productive and impactful research group focused on addressing problems from the clinic with innovations including cell sorter for IVF, optical technologies for detecting viruses, portable point of care technologies for diagnostics in global health, smart robots in vivo, extracellular vesicle based early detection approaches for cancer. He is an elected fellow of the American Institute of Medical and Biological Engineering and The Academy for Radiology & Biomedical Imaging Research Distinguished Investigator.
He has published over 250 peer-reviewed articles, 300 abstracts and proceedings, 24 book chapters and editorials, and 7 edited books. He also serves on the editorial board of various journals. He is a serial academic entrepreneur and co-founded multiple successful companies. His patents are translated into broadly used biomedical products. Dr. Demirci's pioneering work in microfluidics and cell sorting has resulted in CE certified and FDA approved devices used in over 500,000 clinical cases serving patients globally. -
Gaelle Desbordes
Sponsored By Stanford University:, Radiology
BioI am a radiologic data systems engineer at Stanford Medicine Children's Health, helping develop and implement data systems for radiologists with the aim to improve diagnostic accuracy and clinical outcomes.
My previous role was as a senior research engineer at Stanford School of Medicine – Radiology, where I was applying deep learning techniques to enhance the detection and classification of various cancer types in medical images.
I was initially trained as an engineer and research scientist – with an MS in Computer Science, PhD in Cognitive and Neural Systems, and postdoctoral training in computational neuroscience and human brain imaging. More recently, I completed a Professional Certificate in Data Engineering.
Over the course of my career, I have designed, built, and coded computational methods for data analysis, collected and analyzed a range of scientific and clinical data, and effectively communicated research findings to diverse audiences. -
Joseph M. DeSimone
Sanjiv Sam Gambhir Professor of Translational Medicine, Professor of Chemical Engineering and, by courtesy, of Chemistry, of Materials Science and Engineering, and of Operations, Information and Technology at the Graduate School of Business
BioJoseph M. DeSimone is the Sanjiv Sam Gambhir Professor of Translational Medicine and Chemical Engineering at Stanford University. He holds appointments in the Departments of Radiology and Chemical Engineering with courtesy appointments in the Department of Chemistry and in Stanford’s Graduate School of Business.
The DeSimone laboratory's research efforts are focused on developing innovative, interdisciplinary solutions to complex problems centered around advanced polymer 3D fabrication methods. In Chemical Engineering and Materials Science, the lab is pursuing new capabilities in digital 3D printing, as well as the synthesis of new polymers for use in advanced additive technologies. In Translational Medicine, research is focused on exploiting 3D digital fabrication tools to engineer new vaccine platforms, enhanced drug delivery approaches, and improved medical devices for numerous conditions, with a current major focus in pediatrics. Complementing these research areas, the DeSimone group has a third focus in Entrepreneurship, Digital Transformation, and Manufacturing.
Before joining Stanford in 2020, DeSimone was a professor of chemistry at the University of North Carolina at Chapel Hill and of chemical engineering at North Carolina State University. He is also Co-founder, Board Chair, and former CEO (2014 - 2019) of the additive manufacturing company, Carbon. DeSimone is responsible for numerous breakthroughs in his career in areas including green chemistry, medical devices, nanomedicine, and 3D printing. He has published over 350 scientific articles and is a named inventor on over 200 issued patents. Additionally, he has mentored 80 students through Ph.D. completion in his career, half of whom are women and members of underrepresented groups in STEM.
In 2016 DeSimone was recognized by President Barack Obama with the National Medal of Technology and Innovation, the highest U.S. honor for achievement and leadership in advancing technological progress. He has received numerous other major awards in his career, including the U.S. Presidential Green Chemistry Challenge Award (1997); the American Chemical Society Award for Creative Invention (2005); the Lemelson-MIT Prize (2008); the NIH Director’s Pioneer Award (2009); the AAAS Mentor Award (2010); the Heinz Award for Technology, the Economy and Employment (2017); the Wilhelm Exner Medal (2019); the EY Entrepreneur of the Year Award (2019 U.S. Overall National Winner); and the Harvey Prize in Science and Technology (2020). He is one of only 25 individuals elected to all three branches of the U.S. National Academies (Sciences, Medicine, Engineering). DeSimone received his B.S. in Chemistry in 1986 from Ursinus College and his Ph.D. in Chemistry in 1990 from Virginia Tech. -
Terry Desser
Professor of Radiology (Abdominal Imaging), Emerita
Current Research and Scholarly InterestsImaging of gastrointestinal tract cancer
Ultrasound
Simulated learning environment -
Jennifer Dionne
Professor of Materials Science and Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Radiology (Molecular Imaging Program at Stanford)
BioJennifer (Jen) Dionne is a Professor of Materials Science and Engineering and, by courtesy, of Radiology at Stanford. She is also a Chan Zuckerberg Biohub Investigator, deputy director of Q-NEXT (a DOE National Quantum Initiative), and co-founder of Pumpkinseed, a company developing quantum sensors to understand and optimize the immune system. From 2020-2023, Jen served as Stanford’s Inaugural Vice Provost of Shared Facilities, raising capital to modernize instrumentation, fund experiential education, foster staff development, and support new and existing users of the shared facilities. Jen received her B.S. degrees in Physics and Systems Science and Mathematics from Washington University in St. Louis, her Ph. D. in Applied Physics at the California Institute of Technology in 2009, and her postdoctoral training in Chemistry at Berkeley. As a pioneer of nanophotonics, she is passionate about developing methods to observe and control chemical and biological processes as they unfold with nanometer scale resolution, emphasizing critical challenges in global health and sustainability. Her research has developed culture-free methods to detect pathogens and their antibiotic susceptibility; amplification-free methods to detect and sequence nucleic acids and proteins; and new methods to image light-driven chemical reactions with atomic-scale resolution. Jen’s work has been featured in NPR, the Economist, Science, and Nature, and recognized with the NSF Alan T. Waterman Award, a NIH Director’s New Innovator Award, a Moore Inventor Fellowship, and the Presidential Early Career Award for Scientists and Engineers. She was also featured on Oprah’s list of “50 Things that will make you say ‘Wow’!”. She also perceives outreach as a critical component of her role and frequently collaborates with visual and performing artists to convey the beauty of science to the broader public.
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Bao Do
Clinical Professor, Radiology
BioBao Do is an expert in radiology informatics, computer vision, and quantitative musculoskeletal imaging. He has developed and validated deep-learning models for diagnostic interpretation, hardware recognition, and automated reporting across orthopedic and radiographic domains. His recent studies demonstrated high-performance CNNs for detecting perilunate and lunate dislocations on wrist radiographs (AUC = 0.986) 【Pridgen et al., Plast Reconstr Surg 2023; 10.1097/PRS.0000000000010928】 and improving clinician accuracy through machine-learning-assisted diagnosis in a multicenter reader study 【Luan et al., Hand (N Y)2025; 10.1177/15589447241308603】. He co-developed AI systems for automated classification of hip hardware achieving radiologist-level accuracy (AUC ≥ 0.99) 【Ma et al., J Imaging Informat Med 2024; 10.1007/s10278-024-01263-y】, scoliosis curvature measurement from 2,150 spine radiographs 【Ha et al., J Digit Imaging 2022; 10.1007/s10278-022-00595-x】, and fully automated leg-length analysis and reporting 【Larson et al., J Digit Imaging2022; 10.1007/s10278-022-00671-2】. Earlier work included Bayesian models for bone tumor diagnosis 【Do et al., J Digit Imaging 2017; 30:709-13】, semantic content-based image retrieval using relevance feedback 【Banerjee et al., J Biomed Inform 2018; 84:123-35】, and NLP-based uncertainty detection in radiology reports 【Callen et al., J Digit Imaging 2020; 33:1209-19】, demonstrating a career-long commitment to explainable, data-driven imaging analytics.
Interests: Automation in medicine, quantitative MSK AI, MSK tumor AI, AI in workflow, and computer systems in education, QC, research
www.stanford.edu/~baodo -
Robert Dodd, MD, PhD
Associate Professor of Neurosurgery, of Radiology and, by courtesy, of Otolaryngology - Head & Neck Surgery (OHNS)
Current Research and Scholarly InterestsDr. Dodd is involved in clinical trials using endovascular coils that have a fiber coating that help heal aneurysms of the neck and can prevent an aneurysm from reforming. He uses minimally invasive endoscopic techniques to treat brain tumors.
Dodd's research interests are in cerebral blood vessel reactivity and stroke. -
Gozde Durmus
Assistant Professor (Research) of Radiology (Molecular Imaging Program at Stanford)
Current Research and Scholarly InterestsDr. Durmus' research focuses on applying micro/nano-technologies to investigate cellular heterogeneity for single-cell analysis and personalized medicine. At Stanford, she is developing platform technologies for sorting and monitoring cells at the single-cell resolution. This magnetic levitation-based technology is used for wide range of applications in medicine, such as, label-free detection of circulating tumor cells (CTCs) from blood; high-throughput drug screening; and rapid detection and monitoring of antibiotic resistance in real-time. During her PhD, she has engineered nanoparticles and nanostructured surfaces to decrease antibiotic-resistant infections.
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Daniel Bruce Ennis
Professor of Radiology (Veterans Affairs) and, by courtesy, of Bioengineering
Current Research and Scholarly InterestsThe Cardiac MRI Group seeks to invent and validate methods to quantify cardiac performance. We develop methods to measure cardiac structure (DWI/DTI), function (tagging and DENSE), flow (PC-MRI), and remodeling (diffusion, T1-mapping, fat-water mapping) for pediatrics and adults.
Fundamental to our research is a set of tools for numerically optimizing gradient waveforms, Bloch simulations, and patient-specific 3D-printed cardiovascular structures connected to computer controlled flow pumps. -
Ahmet Görkem Er
Postdoc Res Affiliate, Rad/Integrative Biomedical Imaging Informatics at Stanford
Postdoc Res Affiliate-2, Rad/Integrative Biomedical Imaging Informatics at StanfordBioAhmet Görkem Er, M.D., Ph.D., is a physician-scientist and postdoctoral fellow in Integrative Biomedical Imaging Informatics (IBIIS) at Stanford University. He graduated from Istanbul University Faculty of Medicine and completed dual residency training in internal medicine and infectious diseases and clinical microbiology at Hacettepe University. He also has a Ph.D. in medical informatics from Middle East Technical University.
As a Fulbright Ph.D. Dissertation Research Grantee (2022–2023), Dr. Er conducted research at the Stanford Center for Biomedical Informatics Research, focusing on multimodal data integration in COVID-19 patients. This work resulted in a publication in NPJ Digital Medicine demonstrating the value of combining clinical, imaging, and viral genomic data for improved disease modeling. He returned to Stanford in 2024 as a visiting researcher and is currently a postdoctoral fellow, where he combines his clinical background with advanced computational methods.
Dr. Er’s research focuses on developing artificial intelligence and multimodal data fusion approaches for complex diseases. His work integrates a broad spectrum of inputs, including medical imaging, histopathology, clinical data, genomics, and spatial transcriptomics, to improve patient stratification and support data-driven clinical decision-making. -
Koray Ertan
Research Engineer, Rad/Radiological Sciences Laboratory
BioKoray Ertan received his B.Sc. degree in Electrical and Electronics Engineering from Bilkent University, Turkey, where he also completed his Ph.D. under the supervision of Prof. Ergin Atalar. During his doctoral studies, he conducted research at the National Magnetic Resonance Research Center (UMRAM) in Turkey. His dissertation focused on the development of novel magnetic resonance imaging (MRI) technologies, including gradient array systems aimed at improving diagnostic image quality, reducing specific absorption rate (SAR), and shortening scan times.
In April 2019, he joined Prof. Brian Rutt’s group at Stanford University as a postdoctoral researcher. Shortly after, in June 2019, he was also appointed as a MINDED postdoctoral fellow. As part of the MINDED program, his research involved developing a system to modulate the permeability of the blood-brain barrier using focused radiofrequency heating from ultra-high field MRI transmit coils, with the goal of enhancing nanomedicine-based treatments for neurodevelopmental disorders.
He is currently a Research Scientist in the Radiological Sciences Laboratory at Stanford. His present work focuses on the design of next-generation head gradient coils and the analysis of peripheral nerve stimulation (PNS) thresholds. He is developing a predictive framework to estimate subject-specific PNS limits using basic demographic data and localizer MRI scans, with the aim of enabling safer and more efficient MRI. -
Zhongnan Fang
Affiliate, Rad/Radiology Finance and Administration
BioDr. Fang is a Principal ML Scientist in the AIDE Lab. His research interests lie in driving AI innovations in medicine, with a focus on AI model design and development, performance and robustness evaluation, and quality monitoring and debugging. Previously, he was a founding member and the Data Science Lead at LVIS corporation, pioneering personalized neurological disease treatment using cutting-edge neuroscience findings and AI technologies.
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Katherine Ferrara
Professor of Radiology (Molecular Imaging Program at Stanford)
Current Research and Scholarly InterestsMy focus is image-guided drug and gene delivery and I am engaged in the design of imaging devices, molecularly-targeted imaging probes and engineered delivery vehicles, drawing upon my education in biology and imaging physics and more than 20 years of experience with the synthesis and labeling of therapeutic particles. My laboratory has unique resources for and substantial experience in synthetic chemistry and ultrasound, CT, MR and PET imaging.
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Dominik Fleischmann
Professor of Radiology (Cardiovascular Imaging)
Current Research and Scholarly InterestsNon-invasive Cardiovascular Imaging
Image Post-processing
Contrast Medium Dynamics -
Benjamin Lewis Franc
Clinical Professor, Radiology - Rad/Nuclear Medicine
BioDr. Franc is a Clinical Professor of Radiology - Nuclear Medicine and Molecular Imaging. He completed his B.S and M.S. in Chemical Engineering at Stanford University, Stanford, CA. He completed his medical school training at University of Southern California, Keck School of Medicine. While conducting his residency at Stanford University, in the Division of Nuclear Medicine and Molecular Imaging, he was also the chief resident. Dr. Franc’s research interests include all aspects of PET-CT as he has nearly 20 years of experience in clinical Nuclear Medicine with particular expertise in PET-CT.
Dr. Franc predominantly publishes and lectures on applications and innovations of PET-CT. He has proficiency in all aspects of PET radiopharmaceutical development, spanning the design of molecules, synthesis of radioligands, and use in animal and human imaging. He also has expertise in quantitative image analysis, development of novel post-processing image reconstruction methods, and the application of artificial intelligence in human diagnostics. Dr. Franc has implemented new radiopharmaceuticals in pre-clinical and clinical research PET imaging as well as for clinical PET with applications in cancer, infectious disease (HIV), and autoimmune disease (RA). He has applied advanced computational techniques, including deep learning, to extract predictive data for prognosis of various cancers and neurodegenerative diseases from molecular imaging modalities.
Since joining the faculty at Stanford in 2018, Dr. Franc has received several awards including the Radiological Society of North America 2019 Margulis Award for Excellence in Research; RSNA 2019 Trainee Research; and Most read article in Radiology 2019. He has accepted the position of Director, Residency Program, Nuclear Medicine and Molecular Imaging as well as the Director, Radiology Value-Based Care Initiative. Dr. Franc has presented more than 40 abstracts at national and international meetings and published more than 90 papers in peer-reviewed publications, as well as 9 book chapters. -
Abantika Ganguly
Basic Life Research Scientist, Rad/Pediatric Radiology
Current Role at StanfordResearch Scientist
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Sergios Gatidis
Associate Professor of Radiology (Pediatric Radiology)
BioDr. Gatidis completed his medical training at the University of Tuebingen / Germany and received his Diploma in Mathematics from from the Universities of Tuebingen and Hagen / Germany. His research is focused on on methods and applications of machine learning for medical data analysis and translation of AI into clinical practice.
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Marios Georgiadis
Instructor, Radiology
BioMarios is an Instructor of Neuroimaging in the Department of Radiology.
His research focuses mainly on studying brain microstructure using cutting edge imaging (advanced X-ray, MRI, optical, and spatial biology approaches), with a particular focus on Alzheimer's disease hippocampi, neurodegeneration, and a special interest in myelin and iron.
He is also actively involved in projects related to imaging and modeling brain trauma, exosome signatures of neurodegeneration, and imaging the brain using advanced forms of electron and light microscopy.
His current research is being supported by NIH, the Alzheimer's Association, the American Society of Neuroradiology, the National Alzheimer's Coordinating Center (NACC), and the Stanford ADRC.
Marios is a mechanical engineer by training (School of Mechanical Engineering, National Technical University of Athens, Greece). His thesis "Closed-loop force control of a haptic surgical simulator", was performed in the Control Systems Lab of Prof. Evangelos Papadopoulos.
In 2011 he obtained his MSc in Biomedical Engineering from ETH Zurich (Swiss Federal Institute of Technology). He performed his thesis in IBM Research on "Advanced pathology using the Microfluidic Probe", under Emmanuel Delamarche and Govind Kaigala, and was awarded the ETH medal for this work.
He completed his PhD in Bone Biomechanics in the lab of Prof. Ralph Muller in ETH Zurich, where he developed X-ray scattering-based methods to investigate bone microstructure in 3D, research that earned him the 2nd Student Award from the European Society for Biomechanics in 2015.
In 2016 he started using imaging methods to study brain microstructure, in the lab of Prof. Markus Rudin, in the Institute for Biomedical Engineering of ETH Zurich. There, he combined X-ray scattering with DTI, histology and CLARITY for studying rodent brain.
In 2017 he joined the MRI Biophysics group of Profs. Els Fieremans and Dmitry Novikov in New York University School of Medicine, to study human and mouse brain microstructure using X-ray scattering and diffusion MRI.
He is in the Translational Neuroimaging lab, headed by Dr Michael Zeineh, since 2019.
His research on myelin in mouse and human brain using X-ray scattering has been supported twice by the Swiss National Science Foundation. -
Pejman Ghanouni, MD, PhD
Professor of Radiology (Body MRI) and, by courtesy, of Neurosurgery, of Obstetrics and Gynecology and of Urology
BioDr. Ghanouni is a board-certified, fellowship-trained diagnostic radiologist with Stanford Health Care Radiology. He is an associate professor in the Department of Radiology, Division of Body MRI at Stanford University School of Medicine, and by courtesy, of Urology, of Neurosurgery, and of Obstetrics and Gynecology.
Dr. Ghanouni is the director of the Stanford Health Care Minimally Invasive MR Interventional Center (MIMRIC) and the Focused Ultrasound Center of Excellence. He is also chief of the Division of Body MRI at Stanford University School of Medicine.
Dr. Ghanouni is recognized around the world for his extensive expertise in using advanced imaging to diagnose, manage, and treat a wide range of conditions and disorders. As a renowned leader in diagnostic and MRI-guided interventional radiology, Dr. Ghanouni creates a customized care plan for each of his patients.
Dr. Ghanouni’s research interests include the latest advances in MR-guided focused ultrasound techniques to treat essential tremor, Parkinson’s disease, prostate cancer, bone tumors, desmoid tumors, and uterine fibroids. An experienced physician-scientist, Dr. Ghanouni has collaboratively led clinical trials and research initiatives that explore treatments for epilepsy, pancreatic cancer, and several types of tumors. Through these clinical trials, Dr. Ghanouni has helped secure FDA approval for many MR-guided focused ultrasound treatments.
His articles have been published in dozens of peer-reviewed medical journals, including Lancet Oncology, Neurology, Investigative Radiology, European Radiology, Journal of Magnetic Resonance Imaging, Journal of Neurosurgery, New England Journal of Medicine, and Radiology. Dr. Ghanouni has been invited to speak at conferences and symposiums all over the nation and the world, including in Rome, Italy; Tel Aviv, Israel; and Riyadh, Saudi Arabia. He is widely regarded for his groundbreaking research as well as his clinical expertise.
Dr. Ghanouni is a member of several professional organizations, including the International Society for Magnetic Resonance in Medicine, the International Society for Therapeutic Ultrasound, and the European Focused Ultrasound Society.
MR-guided focused ultrasound treatment: https://www.youtube.com/watch?v=3Bwq2YxD9eU -
Gary Glover
Professor of Radiology (Radiological Sciences Lab) and, by courtesy, of Psychology and of Electrical Engineering
Current Research and Scholarly InterestsMy present research is devoted to the advancement of functional magnetic resonance imaging sciences for applications in basic understanding of the brain in health and disease. We collaborate closely with departmental clinicians and with others in the school of medicine, humanities, and the engineering sciences.
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Linika Goel
Ph.D. Student in Biomedical Physics, admitted Autumn 2025
BioI am a first-year Biomedical Physics PhD student interested in neuroimaging techniques, data analysis, and the study of brain connectivity. I am committed to advancing diagnostics, treatment, and accessibility of care for neurological and psychiatric conditions.
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Garry Gold
Stanford Medicine Professor of Radiology and Biomedical Imaging
On Partial Leave from 2026-08-02 To 2027-02-15Current Research and Scholarly InterestsMy primary focus is application of new MR imaging technology to musculoskeletal problems. Current projects include: Rapid MRI for Osteoarthritis, Weight-bearing cartilage imaging with MRI, and MRI-based models of muscle. We are studying the application of new MR imaging techniques such as rapid imaging, real-time imaging, and short echo time imaging to learn more about biomechanics and pathology of bones and joints. I am also interested in functional imaging approaches using PET-MRI.
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Michael L. Goris
Professor of Radiology (Nuclear Medicine), Emeritus
Current Research and Scholarly InterestsRadio-immunotherapy. Medical Imaging Processing. Quantification for diagnosis Clinical validations
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Erin Elizabeth Grady
Clinical Professor, Radiology - Rad/Nuclear Medicine
BioErin Grady, MD, CCD, FACNM, FSNMMI is a nuclear medicine physician at Stanford Hospital and Clinics in Stanford, California. She serves as the Interim Division Chief of Nuclear Medicine and Molecular Imaging, Associate Chair of Education and Diversity, Equity and Inclusion, and is program director for the nuclear radiology and nuclear oncology fellowship programs, as well as a coach for the diagnostic radiology program. She is actively involved nationally in the Society of Nuclear Medicine and Molecular Imaging as a Director-at-Large on the SNMMI Board of Directors, and chair of the Government Relations Committee. She serves on the Nuclear Medicine Residency Review Committee for ACGME appeals panel member and assisted with milestone 1.0 development committee for Nuclear Medicine and 2.0 milestone revision committee for Nuclear Radiology at the ACGME. She has been involved in multiple guideline and appropriate use documents on topics related to thyroid cancer (NCCN panel), neuroendocrine tumors, bone scintigraphy, lung scintigraphy and more. In addition, she is a past chair of the American Board of Nuclear Medicine and past president of the American College of Nuclear Medicine. Her areas of research interest include quality, education, radiopharmaceutical therapy and finding answers to clinical questions that arise during the course of practice. She is passionate about education, nuclear medicine’s future, collaboration across specialties, and is a staunch advocate for patients.
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Edward Graves
Professor of Radiation Oncology (Radiation Physics), and by courtesy, of Radiology
Current Research and Scholarly InterestsApplications of molecular imaging in radiation therapy, small animal image-guided conformal radiotherapy, immune responses to radiation, immunotherapy and radiotherapy combinations, image processing and analysis.
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Kip E. Guja, MD PhD
Clinical Assistant Professor, Radiology - Rad/Nuclear Medicine
Current Research and Scholarly InterestsMy current research interests include:
1) PET/MR and PET/CT imaging in children and adults, for oncologic and non-oncologic indications
2) Targeted radionuclide therapy and theragnostics
3) Pre-clinical development and clinical translation of novel radiopharmaceuticals -
H. Henry Guo, MD, PhD
Clinical Professor, Radiology
Current Research and Scholarly InterestsQuantitative CT
AI assisted radiology interpretation
PET imaging of lung diseases
CT imaging biomarkers heart and lung diseases
Quality assurance of ultralow dose CT scans
Post radiation treatment changes of lung tumors
3D printing
