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Super-Resolution 1H Magnetic Resonance Spectroscopic Imaging Utilizing Deep Learning.
Iqbal, Zohaib; Nguyen, Dan; Hangel, Gilbert; Motyka, Stanislav; Bogner, Wolfgang; Jiang, Steve.
Afiliação
  • Iqbal Z; Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, United States.
  • Nguyen D; Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, United States.
  • Hangel G; Christian Doppler Laboratory for Clinical Molecular MR Imaging, Department of Biomedical Imaging and Image-guided Therapy, High Field MR Center, Medical University of Vienna, Vienna, Austria.
  • Motyka S; Christian Doppler Laboratory for Clinical Molecular MR Imaging, Department of Biomedical Imaging and Image-guided Therapy, High Field MR Center, Medical University of Vienna, Vienna, Austria.
  • Bogner W; Christian Doppler Laboratory for Clinical Molecular MR Imaging, Department of Biomedical Imaging and Image-guided Therapy, High Field MR Center, Medical University of Vienna, Vienna, Austria.
  • Jiang S; Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, United States.
Front Oncol ; 9: 1010, 2019.
Article em En | MEDLINE | ID: mdl-31649879
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Oncol Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Oncol Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos