Using Artificial Intelligence for Automatic Segmentation of CT Lung Images in Acute Respiratory Distress Syndrome.

Herrmann, Peter; Busana, Mattia; Cressoni, Massimo; Lotz, Joachim; Moerer, Onnen; Saager, Leif; Meissner, Konrad; Quintel, Michael; Gattinoni, Luciano

Herrmann, Peter; Busana, Mattia; Cressoni, Massimo; Lotz, Joachim; Moerer, Onnen; Saager, Leif; Meissner, Konrad; Quintel, Michael; Gattinoni, Luciano.

Afiliação

Herrmann P; Department of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany.
Busana M; Department of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany.
Cressoni M; Unit of Radiology, IRCCS Policlinico San Donato, Milan, Italy.
Lotz J; Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany.
Moerer O; Department of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany.
Saager L; Department of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany.
Meissner K; Department of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany.
Quintel M; Department of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany.
Gattinoni L; Department of Anesthesiology, DONAUISAR Klinikum Deggendorf, Deggendorf, Germany.

Front Physiol ; 12: 676118, 2021.

Article em En | MEDLINE | ID: mdl-34594233

Palavras-chave

ARDS; DeepLTK; LabVIEW; Maluna; U-Net; deep learning; fully automatic lung segmentation; mechanical ventilation

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

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