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Artificial Intelligence and Texture Analysis in Cardiac Imaging.
Mannil, Manoj; Eberhard, Matthias; von Spiczak, Jochen; Heindel, Walter; Alkadhi, Hatem; Baessler, Bettina.
Afiliación
  • Mannil M; Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland. manoj.mannil@ukmuenster.de.
  • Eberhard M; University Clinic for Radiology, Westfälische Wilhelms-University Muenster and University Hospital Muenster, Albert-Schweitzer-Campus 1, DE-48149, Muenster, Germany. manoj.mannil@ukmuenster.de.
  • von Spiczak J; Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Heindel W; Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Alkadhi H; University Clinic for Radiology, Westfälische Wilhelms-University Muenster and University Hospital Muenster, Albert-Schweitzer-Campus 1, DE-48149, Muenster, Germany.
  • Baessler B; Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Curr Cardiol Rep ; 22(11): 131, 2020 09 10.
Article en En | MEDLINE | ID: mdl-32910325
ABSTRACT
PURPOSE OF REVIEW The aim of this structured review is to summarize the current research applications and opportunities arising from artificial intelligence (AI) and texture analysis with regard to cardiac imaging. RECENT

FINDINGS:

Current research findings suggest tremendous potential for AI in cardiac imaging, especially with regard to objective image analyses, overcoming the limitations of an observer-dependent subjective image interpretation. Researchers have used this technique across multiple imaging modalities, for instance to detect myocardial scars in cardiac MR imaging, to predict contrast enhancement in non-contrast studies, and to improve image acquisition and reconstruction. AI in medical imaging has the potential to provide novel, much-needed applications for improving patient care pertaining to the cardiovascular system. While several shortcomings are still present in the current methodology, AI may serve as a resourceful assistant to radiologists and clinicians alike.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Inteligencia Artificial Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: Curr Cardiol Rep Asunto de la revista: CARDIOLOGIA Año: 2020 Tipo del documento: Article País de afiliación: Suiza

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Inteligencia Artificial Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: Curr Cardiol Rep Asunto de la revista: CARDIOLOGIA Año: 2020 Tipo del documento: Article País de afiliación: Suiza