The developments of the last few years in computational hardware as well as algorithms, in particular the advent of methods suitable for training complex neural networks (Deep Learning), have opened up new possibilities for machine learning and automation in many applications. Magnetic Resonance imaging, postprocessing and interpretation, in fact radiology in general, are no exception.
Can We See the Bottom? A Look into Deep Learning-Based Image Reconstruction
Dominik Nickel, Ph.D. (Principal Key Expert for Sequence and Reconstruction Techniques, Siemens Healthineers, Erlangen, Germany)
Deep Resolve: Unrivaled Speed in MRI
Nicolas Behl, Ph.D. (Siemens Healthineers, Erlangen, Germany)
Musculoskelettal / Body MRI
Deep Learning-Based Reconstruction in Clinical MRI: How We Do it in Tübingen
Saif Afat, M.D.; et al. (Dept. of Diagnostic and Interventional Radiology, Eberhard Karls University Tübingen, Germany)
Clinical User Perspective of Deep Learning Image Reconstruction Techniques (Deep Resolve) for Improved MRI Capabilities
Trina V. Gulay; Brent Carson, M.D.; et al. (Nanaimo Regional General Hospital, Island Health, Nanaimo, BC, Canada)
Clinical Implementation of Deep Learning-Accelerated HASTE and TSE
Judith Herrmann; M.D. (Eberhard Karls University Tuebingen, Germany); Ahmed Othman, M.D. (University Medical Center, Mainz, Germany); et al.
Deep Learning MRI Sequences: The Present and the Future
Saif Afat, M.D.; et al. (Dept. of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Germany)
Pediatric MRI
Deep Resolve in Pediatric MRI
Johan Dehem, M.D. (Jan Yperman Ziekenhuis, Ieper, Belgium)
Neurological MRI
Ultrafast Brain Imaging with Deep-Learning Multi-Shot EPI: Technical Implementation
Bryan Clifford, et al. (Siemens Medical Solutions USA, Boston, MA, USA)
Ultrafast Brain Imaging with Deep Learning Multi-Shot EPI: Preliminary Clinical Evaluation
John Conklin, et al. (Department of Radiology, Massachusetts General Hospital, Boston, MA, USA)
Whole-body MRI
Whole-Body MRI at 1.5T in the Era of Deep Resolve
Will McGuire; Marie Fennessy; Anwar R. Padhani (Paul Strickland Scanner Centre, Mount Vernon Hospital, Northwood, Middlesex, UK)
Initial Experiences Using Deep Resolve Boost to Accelerate Whole-Body Diffusion MRI
Andrea Ponsiglione, PhD (University of Naples Federico II, Naples, Italy); Anwar R. Padhani, MB, BS, FRCP, FRCR; et al.
(Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, UK)
Technology
Deep Resolve Boost and Sharp for Diffusion: ADC Phantom Evaluation
Hyun-Soo Lee, Ph.D.; Thomas Benkert, Ph.D.; et al. (Siemens Healthineers)
Deep Resolve Mobilizing the Power of Networks
Nicolas Behl, Ph.D. (Siemens Healthineers, Erlangen, Germany)
AI-based Fully Automated Global Circumferential Strain in a Large Cohort of Patients Undergoing Stress CMR
Théo Pezel, MD; Jérôme Garot, MD, PhD; et al. (ICPS, Hôpital Privé Jacques Cartier, Massy, France)
Artificial Intelligence: Learning About the Future of Cardiovascular MR
Kerstin Hammernik, Ph.D. (Technical University of Munich, Germany)
and Thomas Küstner, Ph.D. (University Hospital Tübingen, Germany)
The Connected Imaging Instrument
Michael Hansen, Ph.D. (Microsoft Corporation, USA)
ISMRM Lunch Symposium 2021
Artificial Intelligence’s Role in Radiology: Now and in the Future
Michael P. Recht, M.D. (New York University, New York, USA)
Radiomics and AI in Cancer - Approaches and Analysis
Masoom Haider, M.D. (Sinai Health System & University Health Network, Toronto, Canada)
The Future of Digital Technology in Medicine
Mark A. Griswold, M.D. (Case Western Reserve University, Cleveland, OH, USA)
MR Imaging in the Era of Deep Learning
Florian Knoll, Ph.D. (NYU School of Medicine, Center for Advanced Imaging Innovation and Research (CAI2R), New York, NY, USA)
Deep Learning for Parallel MRI Reconstruction: Overview, Challenges, and Opportunities
Kerstin Hammernik, Ph.D.; et al. (Imperial College London, UK)
Deep Learning for Cardiovascular MR Image Reconstruction
Jennifer A. Steeden, Ph.D. (University College London, UK, Lunch Symposium ESMRMB 2019, Rotterdam, NL)
Exploring New Frontiers in MRI
Sascha Daeuber, Ph.D. (Siemens Healthineers, Erlangen, Germany) Siemens Healthineers Lunch Symposium ESMRMB 2019, Rotterdam, NL
“It’s the data, stupid!” – Unlock the Potential of AI/ML in Radiology through Big Data Approaches
Elmar Merkle, M.D. (University Hospital Basel, Switzerland)
Artificial Intelligence in prostate MRI
Kyung Hyun Sung, Ph.D. (University of California, Los Angeles, USA) 10th MAGNETOM World Summit
Artificial Intelligence for MRI
Heinrich von Busch, Ph.D (Siemens Healthineers, Erlangen, Germany)