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Machine learning in whole-body MRI: experiences and challenges from an applied study using multicentre data.
Lavdas, I; Glocker, B; Rueckert, D; Taylor, S A; Aboagye, E O; Rockall, A G.
Afiliação
  • Lavdas I; Imperial College Comprehensive Cancer Imaging Centre (C.C.I.C.), Hammersmith Campus, Commonwealth Building Main Office, Ground Floor, Du Cane Road, London W12 0NN, UK. Electronic address: ilavdas@imperial.ac.uk.
  • Glocker B; Biomedical Image Analysis Group, Department of Computing, Huxley Building, 180 Queen's Gate, Imperial College London, London SW7 2AZ, UK.
  • Rueckert D; Biomedical Image Analysis Group, Department of Computing, Huxley Building, 180 Queen's Gate, Imperial College London, London SW7 2AZ, UK.
  • Taylor SA; Department of Imaging, University College London Hospitals NHS Foundation Trust, Euston Road, London NW1 2BU, UK.
  • Aboagye EO; Imperial College Comprehensive Cancer Imaging Centre (C.C.I.C.), Hammersmith Campus, Commonwealth Building Main Office, Ground Floor, Du Cane Road, London W12 0NN, UK.
  • Rockall AG; Imperial College Comprehensive Cancer Imaging Centre (C.C.I.C.), Hammersmith Campus, Commonwealth Building Main Office, Ground Floor, Du Cane Road, London W12 0NN, UK; Department of Radiology Hammersmith Hospital, Imperial College Healthcare NHS Trust, Du Cane Road, London W12 0NN, UK.
Clin Radiol ; 74(5): 346-356, 2019 05.
Article em En | MEDLINE | ID: mdl-30803815
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Imagem Corporal Total / Aprendizado de Máquina Tipo de estudo: Clinical_trials / Diagnostic_studies / Observational_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Imagem Corporal Total / Aprendizado de Máquina Tipo de estudo: Clinical_trials / Diagnostic_studies / Observational_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article