PET image segmentation using a Gaussian mixture model and Markov random fields

BACKGROUND: Classification algorithms for positron emission tomography (PET) images support computational treatment planning in radiotherapy. Common clinical practice is based on manual delineation and fixed or iterative threshold methods, the latter of which requires regression curves dependent on...

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Detalles Bibliográficos
Autores principales: Layer, Thomas, Blaickner, Matthias, Knäusl, Barbara, Georg, Dietmar, Neuwirth, Johannes, Baum, Richard P, Schuchardt, Christiane, Wiessalla, Stefan, Matz, Gerald
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4545759/
https://www.ncbi.nlm.nih.gov/pubmed/26501811
http://dx.doi.org/10.1186/s40658-015-0110-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4545759/
https://www.ncbi.nlm.nih.gov/pubmed/26501811
http://dx.doi.org/10.1186/s40658-015-0110-7

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