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Research

Yale offers incredible research opportunities. Resident research spans topics in clinical radiology, outcomes research, image processing, artificial intelligence, healthcare policy, and many other fields. We collaborate with numerous clinical departments, basic and translational research centers at the hospital, as well as with faculty across Yale’s other graduate and professional schools.

More than half of Yale trainees present work at RSNA and other major national/international conferences every year. Our residents have consistently won RSNA/ARRS mini-fellowships, travel grants, society funding, and other awards for over two decades. This track record of distinguished work can be traced to a culture of program commitment to research at all levels.

We currently have two residents participating in the ABR Holman Pathway. Two residents are pursuing a PhD concurrent with their clinical training. Three other residents are participating in personalized research tracks designed for their specific career goals. Numerous other trainees have structured research time built into their clinical training.

Yale provides a research infrastructure that facilitates both resident and faculty efforts. Literature review support, meta-analysis management, statistical and data support, computational clusters, as well as graphic design help for publication are available and greatly improve the efficiency of scholarly activity.

A few trainees are highlighted below:

  • Arman Emad Avesta is pursuing a PhD in biomedical engineering and informatics. His research interests include artificial intelligence, traumatic brain injury, and MR image processing. He is working on advanced automated structural analysis of brain imaging under the supervision of Prof. James Duncan. Arman is also a part of the ABR Holman Research Pathway.

  • Julius Chapiro is on a customized in-training-faculty track and co-directs the Yale Interventional Oncology research lab. He functions as an investigator on several federally, foundationally and industry-funded grants that focus on liver cancer interventions and multi-modality liver imaging. His lab develops novel molecular imaging techniques to visualize the tumor microenvironment and the immune system in mouse and rabbit animal models, and conducts translational and clinical research. These initiatives include machine learning and imaging biomarker development.

  • Fabian Laage-Gaupp is also involved in the Interventional Oncology Research Lab as a clinical research track resident. Fabian helped develop the rabbit liver tumor model at Yale and is the lead resident for animal interventions. He conducts both animal studies as well as clinical research. Fabian is also the in-training director of the global outreach program for interventional radiology, member of the Society of Interventional Oncology (SIO) International Outreach committee and focuses on establishing the IR Training program for the nation of Tanzania.

  • Jonathan Langdon has a PhD degree in biomedical engineering from the University of Rochester, having completed his dissertation in ultrasound elastography. Jonathan’s research interests include image/signal processing, computational methods, computer graphics, and machine learning, particularly as they relate to ultrasound imaging and tissue mechanical characterization. As part of the ABR Holman Research Pathway, Jonathan is working with the Image Processing and Analysis Group (IPAG), focusing on optimization of cardiac ultrasound strain imaging as well as continued work in liver elastography. Jonathan also has a research interest in the development of advanced human interfaces for ultrasound acquisition and visualization via virtual and augmented reality.

  • Brian Letzen has a master’s degree in biomedical engineering and is a member of the Yale Interventional Oncology research lab as a clinical research track resident. His work focuses on the application of deep learning to diagnostic imaging of liver tumors and other solid tumors, with specific interest in designing explainable neuronal network outputs. He received the RSNA Resident / Fellow Research Grant to support that research.

  • Kim Seifert has a master of science in neuroscience from the University of Florida and worked in clinical informatics prior to attending medical school.She also participated in the RSNA/ARRS/AUR Introduction to Academic Radiology program during her second year of residency. Kim has engaged in highly collaborative research projects; her co-investigators span the fields of ophthalmology, otolaryngology, neurosurgery, neurology, and emergency medicine. She is a chief resident and plans to pursue a two-year fellowship in Neuroradiology.

  • Faezeh Sodagari is participating in the RSNA/ARRS/AUR Introduction to Academic Radiology program. Her interests are in health systems and cancer outcome research. Before residency, she was a research fellow in quantitative oncologic imaging. This involved treatment response assessment and optimization of CT technique for dose reduction. Faezeh has previously been funded by a grant from Siemens. She was recently selected to participate in the RSNA Value of Imaging through Comparative Effectiveness (VOICE) Program.

  • Long Tu is pursuing a PhD in comparative effectiveness and clinical outcomes research with a focus on diagnostic algorithms in emergency and neuro-imaging. His research interests include neurovascular disease, cost-effectiveness, diagnostic error reduction, and the utility of interdisciplinary collaboration in diagnosis. Long is also a chief resident and the coordinator for resident research in emergency radiology. He will be a combined neuroradiology and research fellow at Yale.

Faculty Research