Analysis of Bone Scans in Various Tumor Entities Using a Deep-Learning-Based Artificial Neural Network Algorithm-Evaluation of Diagnostic Performance.

Wuestemann, Jan; Hupfeld, Sebastian; Kupitz, Dennis; Genseke, Philipp; Schenke, Simone; Pech, Maciej; Kreissl, Michael C; Grosser, Oliver S

Wuestemann, Jan; Hupfeld, Sebastian; Kupitz, Dennis; Genseke, Philipp; Schenke, Simone; Pech, Maciej; Kreissl, Michael C; Grosser, Oliver S.

Afiliación

Wuestemann J; Department of Radiology and Nuclear Medicine, University Hospital Magdeburg, Leipziger Street 44, 39120 Magdeburg, Germany.
Hupfeld S; Department of Radiology and Nuclear Medicine, University Hospital Magdeburg, Leipziger Street 44, 39120 Magdeburg, Germany.
Kupitz D; Department of Radiology and Nuclear Medicine, University Hospital Magdeburg, Leipziger Street 44, 39120 Magdeburg, Germany.
Genseke P; Department of Radiology and Nuclear Medicine, University Hospital Magdeburg, Leipziger Street 44, 39120 Magdeburg, Germany.
Schenke S; Department of Radiology and Nuclear Medicine, University Hospital Magdeburg, Leipziger Street 44, 39120 Magdeburg, Germany.
Pech M; Department of Radiology and Nuclear Medicine, University Hospital Magdeburg, Leipziger Street 44, 39120 Magdeburg, Germany.
Kreissl MC; Research Campus STIMULATE, Otto-von-Guericke University, 39106 Magdeburg, Germany.
Grosser OS; Department of Radiology and Nuclear Medicine, University Hospital Magdeburg, Leipziger Street 44, 39120 Magdeburg, Germany.

Cancers (Basel) ; 12(9)2020 Sep 17.

Article en En | MEDLINE | ID: mdl-32957650

Palabras clave

bone metastases; bone scan; bone scan index; deep learning; radiomics

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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Cancers (Basel) Año: 2020 Tipo del documento: Article País de afiliación: Alemania

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