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Artificial intelligence machine learning-based coronary CT fractional flow reserve (CT-FFRML): Impact of iterative and filtered back projection reconstruction techniques.
Mastrodicasa, Domenico; Albrecht, Moritz H; Schoepf, U Joseph; Varga-Szemes, Akos; Jacobs, Brian E; Gassenmaier, Sebastian; De Santis, Domenico; Eid, Marwen H; van Assen, Marly; Tesche, Chris; Mantini, Cesare; De Cecco, Carlo N.
Afiliación
  • Mastrodicasa D; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology, Division of Cardiovascular Imaging, Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA, USA; Department of Neuro
  • Albrecht MH; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt, Germany.
  • Schoepf UJ; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC, USA. Electronic address: schoepf@musc.edu.
  • Varga-Szemes A; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA.
  • Jacobs BE; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA.
  • Gassenmaier S; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA.
  • De Santis D; Department of Radiological Sciences, Oncology and Pathology, University of Rome "Sapienza", Rome, Italy.
  • Eid MH; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA.
  • van Assen M; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Center for Medical Imaging - North East Netherlands, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
  • Tesche C; Department of Cardiology and Intensive Care Medicine, Heart Center Munich-Bogenhausen, Munich, Germany.
  • Mantini C; Department of Neuroscience and Imaging, Section of Diagnostic Imaging and Therapy - Radiology Division, SS. Annunziata Hospital, "G. d'Annunzio" University, Chieti, Italy.
  • De Cecco CN; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology & Imaging Sciences, Emory University, Atlanta, GA, USA.
J Cardiovasc Comput Tomogr ; 13(6): 331-335, 2019.
Article en En | MEDLINE | ID: mdl-30391256
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de la Arteria Coronaria / Interpretación de Imagen Radiográfica Asistida por Computador / Angiografía Coronaria / Vasos Coronarios / Estenosis Coronaria / Reserva del Flujo Fraccional Miocárdico / Aprendizaje Automático / Angiografía por Tomografía Computarizada Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: J Cardiovasc Comput Tomogr Asunto de la revista: ANGIOLOGIA / CARDIOLOGIA / RADIOLOGIA Año: 2019 Tipo del documento: Article
Texto completo
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de la Arteria Coronaria / Interpretación de Imagen Radiográfica Asistida por Computador / Angiografía Coronaria / Vasos Coronarios / Estenosis Coronaria / Reserva del Flujo Fraccional Miocárdico / Aprendizaje Automático / Angiografía por Tomografía Computarizada Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: J Cardiovasc Comput Tomogr Asunto de la revista: ANGIOLOGIA / CARDIOLOGIA / RADIOLOGIA Año: 2019 Tipo del documento: Article