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Automatic Lung Segmentation and Quantification of Aeration in Computed Tomography of the Chest Using 3D Transfer Learning.
Maiello, Lorenzo; Ball, Lorenzo; Micali, Marco; Iannuzzi, Francesca; Scherf, Nico; Hoffmann, Ralf-Thorsten; Gama de Abreu, Marcelo; Pelosi, Paolo; Huhle, Robert.
Afiliação
  • Maiello L; Pulmonary Engineering Group, Department of Anaesthesiology and Intensive Care Therapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
  • Ball L; Department of Surgical Sciences and Integrated Diagnostics, IRCCS AOU San Martino IST, University of Genoa, Genoa, Italy.
  • Micali M; Department of Surgical Sciences and Integrated Diagnostics, IRCCS AOU San Martino IST, University of Genoa, Genoa, Italy.
  • Iannuzzi F; Department of Surgical Sciences and Integrated Diagnostics, IRCCS AOU San Martino IST, University of Genoa, Genoa, Italy.
  • Scherf N; Department of Surgical Sciences and Integrated Diagnostics, IRCCS AOU San Martino IST, University of Genoa, Genoa, Italy.
  • Hoffmann RT; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
  • Gama de Abreu M; Department of Diagnostic and Interventional Radiology, University Hospital Carl Gustav Dresden, Technische Universität Dresden, Dresden, Germany.
  • Pelosi P; Pulmonary Engineering Group, Department of Anaesthesiology and Intensive Care Therapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
  • Huhle R; Department of Intensive Care and Resuscitation, Anesthesiology Institute, Cleveland Clinic, Cleveland, OH, United States.
Front Physiol ; 12: 725865, 2021.
Article em En | MEDLINE | ID: mdl-35185592
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article