Author ORCID Identifier


Date of Graduation


Document Type

Thesis (MS)

Program Affiliation

Medical Physics

Degree Name

Masters of Science (MS)

Advisor/Committee Chair

David T. Fuentes

Committee Member

James A. Bankson

Committee Member

Jason Stafford

Committee Member

Richard E. Wendt III

Committee Member

Tucker Netherton


The exponential advancement of quantum computing has led to its increasing integration into medical radiology. Quantum-inspired algorithms have helped accelerate magnetic resonance fingerprinting for possible applications in clinic settings. Numerous global initiatives are currently integrating quantum computing into medical radiology and health care applications. Given the potential of quantum computing to enhance clinical care and medical research, we have developed this primer to introduce medical physicists to the realm of quantum computing. In this primer, we explore the application of currently available quantum computing-based auto-contouring methods to image segmentation. These implementations serve as prototypes of existing quantum algorithms tailored for specific quantum hardware, specifically focusing on the auto-contouring of medical imaging. We evaluated these algorithms using a small MRI abdominal dataset comprising 102 patient scans. Our findings suggest that quantum computing for auto-contouring is still in its infancy, with artificial intelligence-based algorithms remaining the preferred choice for auto- contouring in treatment planning.


Quantum Computing, Medical Image Processing, Image Segmentation, autocontouring

Available for download on Thursday, April 24, 2025