Deep Learning–Based Precontrast CT Parcellation for MRI-Free Brain Amyloid PET Quantification
Sign Up to like & getrecommendations! Published in 2025 at "Clinical Nuclear Medicine"
DOI: 10.1097/rlu.0000000000005652
Abstract: Purpose: This study aimed to develop a deep learning (DL) model for brain region parcellation using CT data from PET/CT scans to enable accurate amyloid quantification in 18F-FBB PET/CT without relying on high-resolution MRI. Patients… read more here.
Keywords: deep learning; pet quantification; brain; parcellation ... See more keywords
Influences on PET Quantification and Interpretation
Sign Up to like & getrecommendations! Published in 2022 at "Diagnostics"
DOI: 10.3390/diagnostics12020451
Abstract: Various factors have been identified that influence quantitative accuracy and image interpretation in positron emission tomography (PET). Through the continuous introduction of new PET technology—both imaging hardware and reconstruction software—into clinical care, we now find… read more here.
Keywords: interpretation; quantification interpretation; pet quantification; influences pet ... See more keywords
Enhancing Amyloid PET Quantification: MRI-Guided Super-Resolution Using Latent Diffusion Models
Sign Up to like & getrecommendations! Published in 2024 at "Life"
DOI: 10.3390/life14121580
Abstract: Amyloid PET imaging plays a crucial role in the diagnosis and research of Alzheimer’s disease (AD), allowing non-invasive detection of amyloid-β plaques in the brain. However, the low spatial resolution of PET scans limits the… read more here.
Keywords: pet quantification; using latent; resolution; amyloid pet ... See more keywords