Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes.
Purpose: We developed a machine learning–based classifier for in vivo amyloid positron emission tomography (PET) staging, quantified cortical uptake of the PET tracer by using a machine learning method, and investigated the impact of these amyloid PET parameters on clinical and structural outcomes....
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 47; no. 8; pp. 1971 - 1984 |
|---|---|
| Autores principales: | , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jul2020
|
| Acceso en línea: | Ver este registro en EBSCOhost |