Tess Reynolds
Papers
12
Total Citations
115
H-Index
6
About
Tess Reynolds is a biomedical imaging researcher specializing in cone-beam computed tomography (CBCT), with a particular focus on advancing intraoperative and interventional imaging through innovative scanning trajectories and reconstruction techniques. Her work addresses some of the most pressing challenges in clinical CBCT, including limited fields of view, metal artifacts, and the demands of real-time surgical guidance. Reynolds has made significant contributions to non-circular orbit design for robotic C-arm systems, demonstrating that departing from conventional circular scans can dramatically reduce metal artifacts caused by surgical implants and hardware — a persistent obstacle in orthopedic and spinal procedures. Her development of extended longitudinal and dual-isocenter CBCT scanning protocols has expanded the anatomical coverage available intraoperatively, enabling visualization of long structures previously beyond reach. She has also pioneered work in geometric calibration for non-standard orbits, cardiac CBCT adaptation, 4D respiratory imaging, and deep learning-based reconstruction. Her most-cited paper, a comprehensive 2022 review of source-detector trajectory optimization, has accumulated 46 citations and serves as a key reference in the field. Complementary work on 3D-printed surgical guides derived from CBCT images further illustrates the translational breadth of her research. Reynolds' contributions are shaping the next generation of smarter, more versatile intraoperative imaging systems.
Research Focus
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Top Papers
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