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Deep Learning on Amyloid Positons Emission Tomography
Sponsor: Central Hospital, Nancy, France
Summary
Reducing injected dose and/or acquisition time in amyloid PET imaging would improve comfort, radiation safety and cost-effectiveness in diagnosis and follow-up of patients. This study evaluates the impact of a deep learning-based noise reduction algorithm on visual analysis and Centiloid quantification when simulating reduced injected doses of \[18F\]flutemetamol.
Official title: Impact of Deep Learning-Based Noise Reduction Algorithm on Visual Analysis and Centiloid Quantification in Reduced-Dose and, or Time Acquisition Amyloid PET Imaging
Key Details
Gender
All
Age Range
18 Years - 99 Years
Study Type
OBSERVATIONAL
Enrollment
40
Start Date
2026-05-06
Completion Date
2027-01-30
Last Updated
2026-06-25
Healthy Volunteers
Not specified
Conditions
Locations (3)
CHRU NANCY Brabois, nuclear medicine department
Vandœuvre-lès-Nancy, France
Nancy's hospital
Vandœuvre-lès-Nancy, France
Nuclear medicine department CHRU de NANCY Brabois
Vandœuvre-lès-Nancy, France