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Evan Calabrese

Assistant Professor of Radiology
Radiology, Neuroradiology

Overview


As a physician scientist focused on artificial intelligence (AI) applications for neurologic disease, my ongoing career goal is to combine clinical excellence in neuroradiology with cutting-edge AI research. My primary research interest lies in the use of innovative AI techniques to help extract clinically useful information from multimodal health data with a focus on neuroimaging. Modern neuroimaging studies, most notably multi-sequence MRI, are amongst the largest and most complex types of health data that are routinely acquired for patients with neurologic disorders. I believe that modern AI tools have enormous potential to help extract new, clinically useful information from complex neuroimaging studies, and through integration with other types of health data, will ultimately improve diagnosis, management, and treatment monitoring for patients with neurologic disease.

Current Appointments & Affiliations


Assistant Professor of Radiology · 2022 - Present Radiology, Neuroradiology, Radiology
Assistant Professor of Biomedical Engineering · 2024 - Present Biomedical Engineering, Pratt School of Engineering

Recent Publications


State and Diffusion of National Institutes of Health Funding of AI in Radiology.

Journal Article J Imaging Inform Med · February 11, 2026 Artificial intelligence research has profound implications for the future of radiology, making it essential to understand funding patterns and diffusion rate from the National Institutes of Health (NIH), historically the leading source of biomedical resear ... Full text Link to item Cite

The 2024 Brain Tumor Segmentation Challenge Meningioma Radiotherapy (BraTS-MEN-RT) dataset.

Journal Article Sci Data · January 27, 2026 Meningiomas are the most common primary intracranial tumors, frequently requiring radiotherapy as a part of management. Effective radiotherapy planning for meningiomas necessitates accurate and consistent segmentation of target volumes on MRI, a process th ... Full text Link to item Cite

The Duke University Cervical Spine MRI Segmentation Dataset (CSpineSeg).

Journal Article Sci Data · October 27, 2025 This work describes a publicly available dataset, the Duke University Cervical Spine MRI Segmentation Dataset (CSpineSeg), consisting of 1,255 cervical spine magnetic resonance imaging (MRI) examinations from 1,232 patients collected from the Duke Universi ... Full text Link to item Cite
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Recent Grants


Building and implementing a TBI prognostic model featuring real-time analysis of brain CT images

ResearchCo Investigator · Awarded by National Institute of Neurological Disorders and Stroke · 2022 - 2027

Identifying Vertebral Artery Dissection on CT Using A Deep Learning Vascular Segmentation Model

ResearchPrincipal Investigator · Awarded by Radiological Society of North America · 2025 - 2026

Federated Learning for Postoperative Segmentation of Treated Glioblastoma (FL-PoST)

ResearchPrincipal Investigator · Awarded by American Roentgen Ray Society · 2024 - 2026

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Education, Training & Certifications


Duke University, School of Medicine · 2016 MD./PhD.