Radiology research forum is a long-running lecture series held approximately every two weeks at our Center.
The forum rotates among lectures by distinguished visiting researchers, presentations by partners involved in Collaborative Projects with our faculty, and research reports by scientists from the radiology department at NYU Langone Health, which operates our Center.
Many of the lectures comprise the Seminar in Biomedical Imaging (BMSC-GA 4416), part of the Biomedical Imaging and Technology PhD Training Program.
Upcoming and most recent lectures are shown first.
On-site seminars are held on the 4th floor at 660 First Avenue, unless otherwise noted. For seminars held via Webex, Zoom, and Microsoft Teams, guests from outside our Center may request an invitation link by reaching out to Rania Assas.
Date: May 21, 2025, at noon
Location: 227 E 30TH ST FL 1 RM 120
Northwestern University
This presentation explores recent breakthroughs in artificial intelligence applications for advanced medical imaging analysis in gastroenterology. I will discuss our novel deep learning algorithms developed specifically for pancreatic and hepatic pathologies across MRI and CT modalities. The talk will highlight our computational approaches for detecting and characterizing pancreatic cancer, intraductal papillary mucinous neoplasms (IPMNs), diabetes-related pancreatic changes, and pancreatitis through innovative image segmentation and classification techniques. The presentation will evaluate how these AI-driven methods are transforming diagnostic capabilities, enhancing radiological workflows, and improving clinical decision-making in gastroenterology. Finally, I will address current limitations and future directions for AI integration into gastroenterological practice, emphasizing both technical challenges and potential clinical impact.
Dr. Ulas Bagci is an Associate Professor (with tenure) at the Northwestern University’s Radiology at Chicago, and courtesy Professor at BME and ECE departments of Northwestern, and CRCV of University of Central Florida. His research interests are artificial intelligence, machine learning and their applications in biomedical and clinical imaging. Dr. Bagci has more than 400 peer-reviewed articles on these topics. Previously, he was a staff scientist and lab co-manager at the National Institutes of Health’s radiology and imaging sciences department, center for infectious disease imaging. Dr. Bagci holds three NIH R01 grants (as Principal Investigator), one NIH U01 grant and serves as a steering committee member of AIR (artificial intelligence resource) at the NIH. Dr. Bagci also serves as an area chair for MICCAI for several years and he is an associate editor of top-tier journals in his fields such as IEEE Trans. on Medical Imaging, Medical Physics, and Medical Image Analysis. Prof. Bagci teaches machine learning, advanced deep learning methods, computer and robot vision, and medical imaging courses. He has several international and national recognitions including best paper and reviewer awards.
Date: May 7, 2025, at noon
Location: 227 E 30TH ST FL 1 RM 120
Department of Brain Sciences
Weizmann Institute of Science
Motivated by the increased SNR in ultra-high field, my lab projects include development of new MR pulse sequences for fast and high-resolution MRI and fMRI; quantitative MRI methods; and new materials for tailoring the RF field. In this talk, I will focus on two projects – (i) a new approach to control the RF transmit and receive signals, and (ii) an approach of adapting the EPI sequence timing to control the ghost/sound-levels. In the first project, we established a new framework of MRI-beneficent artificial materials, combining an artificial dielectric with a set of electric and/or magnetic dipoles. This combination provides high flexibility to plan the possible enhancement, as well as a higher efficiency and a very compact structure. The second project aims to deal with the restrictions due to the gradient’s hardware. A well-known challenge in EPI comes from mechanical vibrations, which produce the well-known MRI sounds and can also cause ghosting artifacts (which are exacerbated at ultra-high field). Our new approach includes modeling and prediction of the acoustic frequencies in EPI, enabling us to control the acoustic spectrum in the sequence. We show that we can affect both the sound level and the ghosting by making subtle timing changes to the TEs (in case of multi-echo acquisitions), to the slices, and to the navigator. This way, we adapt the sequence to the gradient hardware, accounting for the mechanical resonances.
Dr. Rita Schmidt is a Senior Scientist in the Department of Brain Sciences, Weizmann Institute of Science. Her unique carrier path has included a career in the industry, developing MRI guided Focused Ultrasound device for non-invasive treatments, followed by a carrier in academy. Her PhD research focused on a novel ultrafast spatiotemporal encoding (SPEN) acquisition scheme, introducing approaches with high robustness to B0 inhomogeneity. Her post-doctoral research, in the Leiden University Medical Center, focused on characterization of methods to tailor the RF field at 7T MRI, including dielectric resonators and metamaterial designs. In 2019, Rita Schmidt established her own lab at the Weizmann Institute, where she develops new tools for human brain MRI and fMRI at ultra-high field. Recent studies include characterization of the effective temporal resolution in functional MRI, methods to reduce artifacts due to physiological fluctuations designing a novel semi-randomized ordering acquisition scheme, fast quantitative (T2) mapping MRI at 7T. Our two recent projects are a new metamaterial design with that offers a flexible control of the RF transmit and receive signals, and an approach of adapting the EPI sequence timing to control the ghost/sound-levels. Publications’ list: Google Scholar
Date: April 30, 2025, at noon
Location: 227 E 30TH ST FL 1 RM 120
Microstructure imaging is an exponentially growing area of quantitative MRI. It offers the unique ability of noninvasively probing vital cellular-level tissue properties that provide key information on human development, aging and neurological disorders. In brain, we have established the so-called “Standard Model” that allows us to convert empirical diffusion parameters into specific white matter microstructural markers that can disentangle diffusion inside versus outside axons, resulting into markers that are specifically sensitive to inflammation, and demyelination or axonal loss. The SM is ready for clinical adoption thanks to optimized diffusion protocols and robust processing pipelines.
To stay at the frontier of the rapidly expanding area of tissue microstructure imaging and neuroimaging, we are thrilled to announce the acquisition of a unique Connectome 2.0 scanner, to be installed at our institution (NYULH) by the end of 2025, with support from the NIH and the department of Radiology. This system will be custom-built by Siemens Healthineers (Erlangen, Germany) and will be equipped with extraordinary gradients: 500mT/m amplitude and 600T/m/s slew rate (to compare, the corresponding parameters of a typical high-end clinical scanner are 80mT/m and 200T/m/s). Such gradients will produce the strongest diffusion encoding necessary to go beyond the SM and resolve the smallest cellular-level features such as axon diameters or soma sizes, their volume fractions, as well as to quantify transmembrane water exchange. The Connectome 2.0 gradients will also enable the highest angular resolution fiber tracking and distortion-free imaging that applies to virtually all neuroimaging modalities, such as functional MRI, perfusion or relaxometry. It will offer exciting opportunities for collaborative research and development, support existing and enable future NIH-funded studies.
Els Fieremans, Ph.D., is Associate Professor at the Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, and holds an affiliate appointment in the Department of Biomedical Engineering, New York University Tandon School of Engineering. She received her master’s degree in physics and PhD in Biomedical Engineering from Ghent University in Belgium, and completed postdoctoral training at NYU. The goal of her research is to leverage quantitative MRI towards specificity on the cellular scale, through biophysical modeling and validation using numerical and physical phantoms, in order to find the earliest and most sensitive markers of disease. Since 2012, Drs Fieremans and Novikov co-direct the MRI Biophysics group, where they combine theory, numerical simulations, model validation and clinical studies, to achieve an overarching goal of transforming MRI from an imaging device to an accurate and precise scientific instrument for measuring microstructural tissue parameters in health and disease. In 2024, both were elected Fellows of the International Society of Magnetic Resonance in Medicine (ISMRM) “For seminal contributions to the understanding of tissue microstructure using diffusion MRI and for the development of key enabling tools for microstructural imaging.”
Date: April 23, 2025, at noon
Location: 227 E 30TH ST FL 1 RM 120
Professor
Johns Hopkins
Chemical exchange saturation transfer (CEST) MRI has been established as an outstanding tool for measuring tissue pH due to exchange-based signal amplification and multiplexed detection. In addition, an FDA approved CT imaging agent, iopamidol, has been shown to display excellent CEST MRI pH sensitivity, enabling translation of this technology to patients. We are interested in identifying suitable patient populations and introducing refinements in this technology to enable translation.
Urinary tract obstructions (UTOs) are blockages that inhibit the flow of urine through its normal path with as many as 245,000 surgeries/year performed in the US to treat these. Imaging plays an important role in the initial diagnosis in the clinic and whether dilation of the renal pelvis and calices represents a functional obstruction that will lead to kidney injury or a non-obstructive process with preserved kidney function. We will show that CEST MRI pH mapping of the kidneys can detect changes in renal excretion and pH homeostasis and distinguish between obstructed and unobstructed kidney as early as one day after obstructions.
Tumors display abnormal proliferation of cells often followed by development of hypoxia - a signatory feature of tumor microenvironment (TME), which is often considered to be a predictive marker of rapid growth, metastases, recurrence and poor survival rates in solid cancers. We have developed a refinement of pH mapping, glucose-stimulated pH mapping, which leverages the established link between hypoxia, glycolytic activity, and acidosis in tumors and evaluated this technology on mouse models of breast cancer with differential expression in hypoxia-inducible factors (HIFs), particularly HIF-1α. We show that our glucose stimulation enhances the differentiation in these models.
Finally, we have acquired IRB approval for iopamidol based CEST MRI pH mapping and have developed a pH mapping protocol based around the starCEST sequence which employs a turbo-field echo (TFE) acquisition, SENSE reconstruction combined with radial and PROPELLER (Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction) k-space sampling. We will present our initial results for pH mapping the kidneys of 5 healthy volunteers.
Dr. Michael T. McMahon has a Ph.D. in Physical Chemistry from University of Illinois at Urbana-Champaign and has been a member of the Radiology Faculty (MR Division) at Johns Hopkins since 2003 where he is currently Full Professor. He is recognized internationally for his work on chemical exchange saturation transfer (CEST) MRI contrast agents including as a President’s International Fellow of the Chinese Academy of Sciences. He is the lead editor of the only textbook on CEST MRI: “Chemical Exchange Saturation Transfer Imaging: Advances and Applications”. Furthermore, in recognition of his substantial achievements in CEST MRI, Dr. McMahon was elected as Secretary, Vice Chair and Chair of ISMRM’s Molecular Imaging Study Group Study Group, served on ISMRM’s workshop organizing committee, is on the editorial board for Tomography and was previously on the editorial board for Concepts in Magnetic Resonance.
Date: April 17, 2025, at noon
Location: 227 E 30TH ST FL 7 RM 717 and via Zoom
Assistant Professor of Radiology
Co-Director of the Imaging Research Core Case Western Reserve University
Magnetic resonance imaging (MRI) plays a critical role in diagnosis and staging of various pathologies. Traditional MRI techniques rely on a set of contrast-weighted images, which limit their capability to provide a more comprehensive assessment for clinical diagnosis and treatment monitoring. Magnetic Resonance Fingerprinting (MRF) is an advanced quantitative MRI method, which can provide rapid and accurate quantification of multiple tissue properties. My research focuses on developing and translating the MRF technique for body imaging. The developed methods have demonstrated superior performance in both repeatability and reproducibility compared to existing quantitative MRI methods. In this presentation, I will introduce recent technical advances in MRF, followed by findings from multiple clinical studies.
Date: April 16, 2025, at 11:30 a.m.
Location: 227 E 30TH ST FL 1 RM 120 and via Zoom
Postdoctoral Researcher
Stanford Unviersity
This presentation explores the growing role of AI in biomedical research, focusing on two innovative advancements. First, GPT-RadPlan, an AI-driven framework, fully automates radiotherapy treatment planning, consistently outperforming traditional methods by leveraging large multimodal language models like GPT-4V. Second, we introduce TextGrad, a framework that optimizes AI agentic systems using natural language feedback from large language models, applicable across various domains, including biomedical research. Together, these tools demonstrate the potential of AI to revolutionize clinical decision-making and advance the field of biomedical research.
Date: April 3, 2025, at 2:00 p.m.
Location: 60 5TH AVE RM 150 and via Zoom
Machine Learning Researcher
Calico Life Sciences
There is a regulatory code written in DNA and RNA sequences that controls gene expression and isoform processing. Developing accurate models of this code is crucial for advancing human health – such models allow us to interpret harmful genetic mutations and design improved regulatory sequences. In this talk, I will first give an overview of existing machine learning methods for sequence-based prediction of regulatory functions (transcription, RNA splicing, etc.). I will then present a unified model of gene regulation that directly learns to predict raw RNA expression profiles from DNA sequence alone. In the second part of the talk, I will discuss methods for designing improved regulatory sequences and highlight their potential for molecular therapies. I will conclude by discussing future opportunities and challenges in developing even better models of gene expression..
Date: March 26, 2025, at noon
Location: 227 E 30TH ST FL 1 RM 120 and via Zoom
PhD Candidate
Electrical Engineering and Computer Sciences
University of California at Berkeley
Acoustic noise is well-acknowledged as a major source of patient discomfort during MRI scans, and quiet scans have been shown to improve exam success rates. In this work, we demonstrate the feasibility of quiet DCE-MRI using zero echo-time (ZTE) imaging, which offers a unique combination of high scan efficiency and low acoustic noise. Specifically, we address two main challenges of using ZTE for DCE applications: (1) dominant PD-weighting and (2) poor temporal k-space sampling. To overcome these limitations, we first increase T1-weighting using phase-modulated RF pulses and a corresponding inverse problem-based reconstruction, which enables quiet post-contrast imaging. Next, we improve temporal k-space sampling using Arc-ZTE, a method that continuously slews the gradients to achieve improved k-space coverage with minimal gradient refocusing. Arc-ZTE allows for flexible and quiet dynamic imaging, which we demonstrate by visualizing contrast uptake in a custom-built phantom. Overall, these advancements enable significantly improved patient cooperation and comfort, especially for neonates and young pediatric patients.
Date: March 19, 2025, at noon
Location: 227 E 30TH ST FL 1 RM 120 and via Zoom
Assistant Professor
Mechanical Engineering
Binghamton University (State University of New York)
Cortical folding is a fundamental process in human brain development, driven by the complex interplay between mechanical forces, tissue growth, and connectivity establishment. As the cerebral cortex expands significantly in volume and surface area, it undergoes extensive gyrification, which is essential for efficient neural wiring and cognitive function. Disruptions in this process have been implicated in neurodevelopmental disorders, including autism spectrum disorder (ASD), epilepsy, and schizophrenia, where abnormal folding patterns are often accompanied by structural connectivity impairments. Despite growing evidence linking cortical morphology to brain connectivity, the underlying mechanisms governing this relationship remain largely unknown.
In this talk, I will present our latest findings on the multiscale mechanics of brain growth, folding, and connectivity development. We will explore how mechanical forces shape cortical morphology and contribute to the organization of neural circuits, as well as how deviations from these processes may lead to pathological conditions. Using an integrated approach that combines neuroimaging, multiscale computational modeling, and deep learning techniques, we aim to uncover the fundamental principles governing cortical folding and its role in healthy and disordered brain development. Furthermore, I will discuss our recent insights into the structure-property relationships of brain tissue from the microscale to the macroscale, shedding light on how mechanical properties influence cortical architecture and connectivity. These findings provide a critical foundation for understanding the origins of abnormal development associated with neurodevelopmental disorders.
Date: March 5, 2025, at noon
Location: 227 E 30TH ST FL 1 RM 120 and via Zoom
Assistant Professor
Department of Psychiatry, NYU Grossman School of Medicine
NYU Langone Center for Psychedelic Medicine
Dr. Joshua Siegel’s work has focused on developing precision functional mapping (PFM) and applying it to understand the mechanism of psychoactive drugs. Part 1 will present a recently published study showing that psilocybin, the psychedelic found in magic mushrooms, drives widespread desynchronization of brain activity across spatial scales (local, areal, global). Part 2 will discuss implementation of advanced fMRI and PFM tools at NYU Langone, including some sequence testing and pilot data.
Date: Februrary 19, 2025, at noon
Location: 227 E 30TH ST FL 1 RM 120 and via Zoom
Research Assistant Professor
Albert Einstein College of Medicine and Montefiore Medical Center
The incidence of loneliness has increased over the past several decades worldwide and is particularly common among people with serious mental illnesses. However, this major public health problem has been difficult to address, in part because the neural and cognitive mechanisms underlying loneliness are poorly understood. This talk will discuss research on the neurobiological correlates of loneliness and isolation in those with psychotic spectrum disorders using ASL and fMRI techniques alongside peripheral biomarkers in two independent samples.
Date: Februrary 5, 2025, at noon
Location: 227 E 30TH ST FL 1 RM 120 and via Zoom
Staff Scientist, Siemens Healthineers
Collaborations Scientist, NYU Langone Health
This talk will provide an overview of the Free.Max 0.55T scanner that was recently installed at the 22nd Street Gramercy imaging facility. Details of the system with a focus on available hardware and software features will be presented. This will include information on product pulse sequences and supported WIP packages along with examples of various imaging applications.
Date: January 22, 2025, at noon
Location: 227 E 30TH ST FL 1 RM 120 and via Zoom
Postdoctoral Fellow
Department of Radiology
NYU Grossman School of Medicine
Hepatic encephalopathy is a severe complication of chronic or acute liver disease causing toxin accumulation in the brain, but its structural and neurometabolic consequences are still poorly understood. Following a general introduction about MR spectroscopy (MRS) and the current clinical trends of the field, I will present the two main results of my PhD work. In a rat model of hepatic encephalopathy, we measured: (1) altered cerebellar microstructure using diffusion-weighted MRS and diffusion MRI and (2) down-regulated glucose metabolism using FDG-PET and downfield 1H MRS at 14.1 T. Methodological developments regarding MR sequence design and PET quantification that enabled these findings will be described alongside. Finally, our first implementation of diffusion MRS at CBI will be presented, comparing the “stick compartment” in human brain as derived from diffusion MRS and diffusion MRI.
Researchers at the Center for Biomedical Imaging at NYU Langone Health develop transformative imaging technologies to advance basic science and address unsolved clinical problems.
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