The aim of this study was to implement a Dirichlet process mixture (DPM) model for automatic tumor edge identification on (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) images by optimizing the parameters on which the algorithm depends, to validate it experimentally, and to test its robustness.

A Dirichlet process mixture model for automatic (18)F-FDG PET image segmentation: Validation study on phantoms and on lung and esophageal lesions

GIRI, MARIAGRAZIA;CAVEDON, CARLO;Mazzarotto, Renzo;FERDEGHINI, Marco
2016-01-01

Abstract

The aim of this study was to implement a Dirichlet process mixture (DPM) model for automatic tumor edge identification on (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) images by optimizing the parameters on which the algorithm depends, to validate it experimentally, and to test its robustness.
2016
Dirichlet process mixture (DPM) , (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/941157
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