Author/Authors :
Meyer-Base, Anke Department of Scientific Computing - Florida State University - Tallahassee - Florida, USA , Morra, Lia Dipartimento di Automatica e Informatica - Politecnico di Torino - Torino, Italy , Meyer-Base, Uwe Department of Electrical and Computer Engineering - Florida A&M University and Florida State University - Tallahassee - Florida, USA , Pinker, Katja Department of Radiology - Memorial Sloan-Kettering Cancer Center - New York, USA
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.
