Key Principles and Recommendations from TG-381
Radiopharmaceuticals, Theranostics, and Nuclear Medicine
Invited Program · Radiopharmaceuticals, Theranostics, and Nuclear Medicine
Author profile
Department of Radiology, University of Michigan
Radiopharmaceuticals, Theranostics, and Nuclear Medicine
Artificial intelligence-based denoising has shown much promise in improving signal-to-noise in medical imaging. Our goal was to optimize Y-90 bremsstrahlung SPECT imaging following transarterial radioembolization (TARE) using a deep learning-based denoising m...
Radiopharmaceuticals, Theranostics, and Nuclear Medicine