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Deep learning-based denoising of low-dose SPECT myocardial perfusion images: quantitative assessment and clinical performance.
Aghakhan Olia, Narges; Kamali-Asl, Alireza; Hariri Tabrizi, Sanaz; Geramifar, Parham; Sheikhzadeh, Peyman; Farzanefar, Saeed; Arabi, Hossein; Zaidi, Habib.
Afiliação
  • Aghakhan Olia N; Department of Medical Radiation Engineering, Shahid Beheshti University, Tehran, Iran.
  • Kamali-Asl A; Department of Medical Radiation Engineering, Shahid Beheshti University, Tehran, Iran. a_kamali@sbu.ac.ir.
  • Hariri Tabrizi S; Department of Medical Radiation Engineering, Shahid Beheshti University, Tehran, Iran.
  • Geramifar P; Research Center for Nuclear Medicine, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran.
  • Sheikhzadeh P; Department of Nuclear Medicine, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran.
  • Farzanefar S; Department of Nuclear Medicine, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran.
  • Arabi H; Division of Nuclear Medicine and Molecular Imaging, Department of Medical Imaging, Geneva University Hospital, CH-1211, Geneva 4, Switzerland.
  • Zaidi H; Division of Nuclear Medicine and Molecular Imaging, Department of Medical Imaging, Geneva University Hospital, CH-1211, Geneva 4, Switzerland. habib.zaidi@hcuge.ch.
Eur J Nucl Med Mol Imaging ; 49(5): 1508-1522, 2022 04.
Article em En | MEDLINE | ID: mdl-34778929
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Observational_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Observational_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article