Juliet Li

Juliet Li is a PhD-qualified researcher affiliated with the School of Physics, Mathematics and Computing, focusing on advanced medical imaging techniques. Her work bridges computational physics and clinical cardiology through rigorous quantitative analysis.

Her research specializes in radiomics methodology development and AI validation for cardiac imaging, particularly investigating reproducibility challenges in coronary artery segmentation using [18F]NaF PET/CT. Key interests include artificial intelligence integration in diagnostic workflows, fluorine-18 tracer applications, and meta-analytical approaches to radiomics quality assessment. The fingerprint analysis confirms deep engagement with Positron Emission Tomography, Coronary Artery analysis, and systematic review frameworks.

Scientific contributions include:

• Development of auto-segmentation protocols for coronary arteries
• Critical evaluation of radiomics quality scoring systems
• Reproducibility studies comparing manual vs. AI-derived segmentation

Her publication record demonstrates active collaboration with clinical researchers across cardiology and nuclear medicine, with recent work emphasizing methodological rigor in translational imaging research. Current projects appear focused on establishing standardized radiomics pipelines for cardiac PET/CT applications.