Evaluating a Machine Learning Tool for the Classification of Pathological Uptake in Whole-Body PSMA-PET-CT Scans

The importance of machine learning (ML) in the clinical environment increases constantly. Differentiation of pathological from physiological tracer-uptake in positron emission tomography/computed tomography (PET/CT) images is considered time-consuming and attention intensive, hence crucial for diagn...

Descripción completa

Detalles Bibliográficos
Autores principales: Erle, Annette, Moazemi, Sobhan, Lütje, Susanne, Essler, Markus, Schultz, Thomas, Bundschuh, Ralph A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8396250/
https://www.ncbi.nlm.nih.gov/pubmed/34449727
http://dx.doi.org/10.3390/tomography7030027

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8396250/
https://www.ncbi.nlm.nih.gov/pubmed/34449727
http://dx.doi.org/10.3390/tomography7030027

Ejemplares similares