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Artificial intelligence, machine (deep) learning and radio(geno)mics: definitions and nuclear medicine imaging applications.
Visvikis, Dimitris; Cheze Le Rest, Catherine; Jaouen, Vincent; Hatt, Mathieu.
Afiliación
  • Visvikis D; LaTIM, INSERM UMR 1101, IBRBS, Faculty of Medicine, Univ Brest, 22 avenue Camille Desmoulins, 29238, Brest, France. dimitris@univ-brest.fr.
  • Cheze Le Rest C; LaTIM, INSERM UMR 1101, IBRBS, Faculty of Medicine, Univ Brest, 22 avenue Camille Desmoulins, 29238, Brest, France.
  • Jaouen V; Nuclear Medicine Department, CHU Milétrie, Poitiers, France.
  • Hatt M; LaTIM, INSERM UMR 1101, IBRBS, Faculty of Medicine, Univ Brest, 22 avenue Camille Desmoulins, 29238, Brest, France.
Eur J Nucl Med Mol Imaging ; 46(13): 2630-2637, 2019 Dec.
Article en En | MEDLINE | ID: mdl-31280350
ABSTRACT
Techniques from the field of artificial intelligence, and more specifically machine (deep) learning methods, have been core components of most recent developments in the field of medical imaging. They are already being exploited or are being considered to tackle most tasks, including image reconstruction, processing (denoising, segmentation), analysis and predictive modelling. In this review we introduce and define these key concepts and discuss how the techniques from this field can be applied to nuclear medicine imaging applications with a particular focus on radio(geno)mics.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Imagen Molecular / Aprendizaje Profundo / Medicina Nuclear Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Eur J Nucl Med Mol Imaging Asunto de la revista: MEDICINA NUCLEAR Año: 2019 Tipo del documento: Article País de afiliación: Francia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Imagen Molecular / Aprendizaje Profundo / Medicina Nuclear Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Eur J Nucl Med Mol Imaging Asunto de la revista: MEDICINA NUCLEAR Año: 2019 Tipo del documento: Article País de afiliación: Francia