Improving diagnostic precision in amyloid brain PET imaging through data-driven motion correction.
Hye Lim ParkSonya Youngju ParkMingeon KimSoyeon PaengEun Jeong MinInki HongJudson JonesEun Ji HanPublished in: EJNMMI physics (2024)
The motion correction algorithm provided better image quality and higher interobserver agreement. Therefore, we suggest that this algorithm be adopted as a routine post-processing protocol in amyloid brain PET/CT imaging and applied to brain PET scans with other radiotracers.
Keyphrases
- pet ct
- pet imaging
- positron emission tomography
- computed tomography
- resting state
- image quality
- white matter
- machine learning
- functional connectivity
- deep learning
- cerebral ischemia
- randomized controlled trial
- high resolution
- high speed
- multiple sclerosis
- magnetic resonance imaging
- mass spectrometry
- fluorescence imaging
- neural network
- blood brain barrier
- contrast enhanced