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Current Status and Future Perspectives of Artificial Intelligence in Magnetic Resonance Breast Imaging.
Meyer-Bäse, Anke; Morra, Lia; Meyer-Bäse, Uwe; Pinker, Katja.
Affiliation
  • Meyer-Bäse A; Department of Scientific Computing, Florida State University, Tallahassee, Florida 32310-4120, USA.
  • Morra L; Dipartimento di Automatica e Informatica, Politecnico di Torino, Torino, Italy.
  • Meyer-Bäse U; Department of Electrical and Computer Engineering, Florida A&M University and Florida State University, Tallahassee, Florida 32310-4120, USA.
  • Pinker K; Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Vienna, Austria.
Contrast Media Mol Imaging ; 2020: 6805710, 2020.
Article in En | MEDLINE | ID: mdl-32934610
ABSTRACT
Recent advances in artificial intelligence (AI) and deep learning (DL) have impacted many scientific fields including biomedical maging. Magnetic resonance imaging (MRI) is a well-established method in breast imaging with several indications including screening, staging, and therapy monitoring. The rapid development and subsequent implementation of AI into clinical breast MRI has the potential to affect clinical decision-making, guide treatment selection, and improve patient outcomes. The goal of this review is to provide a comprehensive picture of the current status and future perspectives of AI in breast MRI. We will review DL applications and compare them to standard data-driven techniques. We will emphasize the important aspect of developing quantitative imaging biomarkers for precision medicine and the potential of breast MRI and DL in this context. Finally, we will discuss future challenges of DL applications for breast MRI and an AI-augmented clinical decision strategy.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Image Processing, Computer-Assisted / Breast Neoplasms / Artificial Intelligence / Magnetic Resonance Imaging Type of study: Prognostic_studies Limits: Animals / Female / Humans Language: En Journal: Contrast Media Mol Imaging Journal subject: DIAGNOSTICO POR IMAGEM Year: 2020 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Image Processing, Computer-Assisted / Breast Neoplasms / Artificial Intelligence / Magnetic Resonance Imaging Type of study: Prognostic_studies Limits: Animals / Female / Humans Language: En Journal: Contrast Media Mol Imaging Journal subject: DIAGNOSTICO POR IMAGEM Year: 2020 Type: Article Affiliation country: United States