ISMRM Workshop Series • 14-17 MARCH 2018
Back

ISMRM Workshop on
Machine Learning
Asilomar Conference Grounds, Pacific Grove, CA, USA

Program
Registration & Setup – Wednesday, 14 March 2018 – No CME Available
15:00   Registration & Speaker Upload Available
18:00   Welcome Dinner
 
Day 1 – Thursday, 15 March 2018 – No CME Available
07:30   Breakfast served until 9:00
Registration & Speaker Upload Available
 
Session 1: Overview of Machine Learning Methods
  Moderators: Enhao Gong, M.Sc. & Daniel Rueckert, Ph.D.
08:30   Welcome Greg Zaharchuk, M.D., Ph.D.
Stanford University
Stanford, CA, USA
08:40 Machine Learning: Historical Perspectives Kyunghyun Cho, Ph.D.
New York University
New York, NY, USA
09:00     State-of-the-Art Methods in Supervised Machine Learning - Permission Withheld Song Han, Ph.D.
Stanford University
Stanford, CA, USA
09:20   State-of-the-Art Unsupervised Machine Learning Approaches Taesung Park, M.S.
University of California, Berkeley
Berkeley, CA, USA
09:40   Democratizing Deep Learning Across Industries via Open-Source Software Yangqing Jia, Ph.D.
Facebook
Menlo Park, CA, USA
10:00   Learning Beyond Human Experts Stella Yu, Ph.D.
University of California, Berkeley
Berkeley, CA, USA
10:20   Break, Poster Viewing & Speaker Upload Available  
 
Session 2: Reconstruction 1
  Moderators: Florian Knoll, Ph.D. & Jo Schlemper, M.Res.
10:50   Overview of Machine Learning Methods for Reconstruction of Imaging Data Kerstin Hammernik, M.Sc.
Graz University of Technology
Graz, Austria
  Proffered Papers - Oral Session
11:10 Scan-Specific Deep Learning with Robust Artifical-Neural-Networks for k-space Interpolation (RAKI) for Improved Parallel Imaging Mehmet Akcakaya, Ph.D.
University of Minnesota
Minneapolis, MN, USA
11:20 AUTOmated Pulse SEQuence Generation (AUTOSEQ) Using Bayesian Reinforcement Learning in an MRI Physics Simulation Environment Bo Zhu, Ph.D.
A.A. Martinos Center for Biomedical Imaging
Charlestown, MA, USA
11:30 Generative Adversarial Networks for Compressed Sensing (GANCS) MRI Morteza Mardani, Ph.D.
Stanford University
Stanford, CA, USA
11:40 Data-Cycle-Consistent Adversarial Networks for High-Quality Reconstruction of Undersampled MRI Data Fang Liu, Ph.D.
University of Wisconsin - Madison
Madison, WI, USA
11:50 k-space-Aware Convolutional Sparse Coding: Learning from Undersampled k-space Datasets for Reconstruction Frank Ong, B.S.
University of California, Berkeley
Berkeley, CA, USA
12:00   Lunch & Speaker Upload Available
 
Session 3: Post-Processing Methods
  Moderators: Jong Chul Ye, Ph.D. & Fang Liu, Ph.D.
13:00   Power Pitch Session
  Proffered Papers - Oral Session
13:40 Off-ResNet: Deep Residual Network for Non-Stationary Off-Resonance Artifact Correction David Zeng, M.S.
Stanford University
Stanford, CA, USA
13:50 Game of Learning Bloch Equation Simulations for MR Fingerprinting Mingrui Yang, Ph.D.
Case Western Reserve University
Cleveland, OH, USA
14:00 Direct Contrast Synthesis for Magnetic Resonance Fingerprinting Patrick Virtue, B.S.
University of California, Berkeley
Berkeley, CA, USA
14:10 Accelerated Multi-Shot EPI Through Machine Learning & Joint Reconstruction Berkin Bilgic, Ph.D.
A.A. Martinos Center for Biomedical Imaging
Boston, MA, USA
14:20 Analysis of the Influence of Deviations Between Training & Test Data in Learned Image Reconstruction Florian Knoll, Ph.D.
New York University
New York, NY, USA
14:30 Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction Chen Qin, Ph.D. student
Imperial College London
London, England, UK
14:40 Applications of Deep Learning for PET/MRI Alan McMillan, Ph.D.
University of Wisconsin - Madison
Madison, WI, USA
15:00 Machine Learning in Medical Image Registration Xiaohuan Cao, M.S.
University of North Carolina
Chapel Hill, NC, USA
15:20   Break, Poster Viewing & Speaker Upload Available
 
Session 4: Power Pitch Session
  Moderators: Matthew Rosen, Ph.D. & Chun Yuan, Ph.D.
  Proffered Papers - Oral Session
16:00 Simultaneous Relaxometry & Segmentation of Human Brain Through a Deep Neural Network Peng Cao, Ph.D.
University of California, San Francisco
San Francisco, CA, USA
16:10 Using U-Nets with Morphological MR Inputs for Ultra-Low-Dose Amyloid PET Reconstruction Kevin Chen, Ph.D.
Stanford University
Stanford, CA, USA
16:20 Data-Driven Synthetic MRI FLAIR Artifact Correction via Deep Neural Network Jiyong Park, B.S.
Yonsei University
Seoul, South Korea
16:30   Power Pitch Session
17:15   Poster Session
18:00   Dinner (served until 19:00)
19:00   Industry Talks
19:45   Social Event
 
Day 2 – Friday, 16 March 2018 – No CME Available
07:30   Breakfast served until 9:00
Registration & Speaker Upload Available
 
Session 5: Clinical Application of Machine Learning
  Moderators: Garry Gold, M.D. & Kathleen Schmainda, Ph.D.
08:30   Keynote: How Machine Learning Will Affect the Future of Clinical Imaging Curtis Langlotz, M.D., Ph.D.
Stanford University
Stanford, CA, USA
09:10   Data Preparation, Labeling & Deployment of Imaging Datasets for Deep Learning Michael Muelly, M.D.
Google
Mountain View, CA, USA
09:30   Panel Discussion  
09:50   Break, Poster Viewing & Speaker Upload Available
 
10:10   Integrating Machine Learning into the Clinical Imaging Workflow & Other Practical Considerations Paul Chang, M.D.
University of Chicago
Chicago, IL, USA
  Proffered Papers - Oral Session
10:30 3D Convolutional Neural Nets for MRI Detection & Severity Staging of Knee Osteoarthritis Degenerative Changes Berk Norman, B.S.
University of California, San Francisco
San Francisco, CA, USA
10:40 Deep-Learning-Based Super-Resolution & Segmentation for Clinical & Research Musculoskeletal MRI Akshay Chaudhari, Ph.D.
Stanford University
Stanford, CA, USA
10:50 QSM with Deep Neural Network Jaeyeon Yoon, Undergraduate
Seoul National University
Seoul, South Korea
11:00 Deep Recurrent Learning of Brain Functional Dynamics for Data-Driven Classification of Psychiatric Diagnosis: The Temporal Template Network Byung-Hoon Kim, M.D., M.S.
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, South Korea
11:10 Bayesian Deep Learning: Model Uncertainty Generation in MR Image Segmentation Gengyan Zhao, M.Sc.
University of Wisconsin - Madison
Madison, WI, USA
11:20 Denoising Arterial Spin Labeling Cerebral Blood Flow Images Using Deep Learning-Based Methods Danfeng Xie, Ph.D.
Temple University
Philadelphia, PA, USA
11:30 Musculoskeletal Applications of Deep Learning Valentina Pedoia, Ph.D.
University of California, San Francisco
San Francisco, CA, USA
11:50   Lunch (served from 12:00-13:00) & Speaker Upload Available
12:45   Nature Hike - Asilomar
 
Session 6: Neuro Applications
  Moderators: Kim Mouridsen, Ph.D. & Greg Zaharchuk, M.D., Ph.D.
14:00     Brain Tumor Segmentation with Multimodal MRI & Deep Learning - Permission Withheld Peter Chang, M.D.
University of California, San Francisco
San Francisco, CA, USA
14:20 Deep Learning for Prediction of Ischemic Stroke Lesion Segmentation Miguel Monteiro, M.Sc.
INESC-ID
Lisbon, Portugal
  Proffered Papers - Oral Session
14:40 Deep Learning Enables Accurate Diagnosis of Parkinson’s Disease Patients Using T1-Weighted Images Alone Ting Yu Su, M.S.
National Cheng Kung University
Tainan, Taiwan
14:50 Sexual Dimorphism in Predictive Models of Brain Volume for Identification of Individuals Prenatally Exposed to Alcohol Graham Little, B.Sc.
University of Alberta
Edmonton, AB, Canada
15:00 Acute Ischemic Stroke Outcome Prediction: Do Perfusion Biomarkers Even Matter? Anne Nielsen, M.Sc.
Aarhus University
Aarhus, Denmark
15:10 Application of Machine Learning to Dementia Saman Sarraf, M.Sc., M.Eng.
Konica Minolta Laboratory U.S.A., Inc.
San Francisco, CA, USA
15:30 Identifying Brain Hemorrhage Using Machine Learning Paras Lakhani, M.D.
Jefferson University Hospitals
Philadelphia, PA, USA
15:50   Break, Poster Viewing & Speaker Upload Available
 
Session 7: Hands-On Deep Learning
  Moderators: Dongwook Lee, M.Sc. & John Pauly, Ph.D.
16:20     Hardware Considerations for Using Machine Learning with Medical Imaging Data - Permission Withheld William Dally, Ph.D.
Stanford University & NVIDIA
Stanford, CA, USA
16:40   Deep Learning Hands-on Demo Peter Chang, M.D.
University of California, San Francisco
San Francisco, CA, USA

Greg Zaharchuk, M.D., Ph.D.
Stanford University
Stanford, CA, USA
18:00   Dinner (served until 19:00)
19:30   Keynote: The Information Bottleneck Theory of Deep Learning Naftali Tishby, Ph.D.
Hebrew University
Jerusalem, Israel
20:30   Adjourn
 
Day 3 – Saturday, 17 March 2018 – No CME Available
07:30   Breakfast served until 9:00
Registration & Speaker Upload Available
 
Session 8: Non-Neuro Applications
  Moderators: Joseph Cheng, Ph.D. & Peder Larson, Ph.D.
08:30 Multimodal Prostate MR Classification Using Machine Learning Alireza Mehrtash, M.S.
Brigham & Women's Hospital
Boston, MA, USA
08:50   Computer-Aided Classification of Benign & Malignant Lesions in the Breast with MRI Natalia Antropova, B.S.
University of Chicago
Chicago, IL, USA
09:10 Applications of Deep Learning to Cardiac MRI: Building Technologies for the Clinical Environment Albert Hsiao, M.D., Ph.D.
University of California, San Diego
San Diego, CA, USA
  Proffered Papers - Oral Session
09:30 Expanding SMS Coverage in Cardiac Perfusion MRI Through Deep Learning for Temporal Interpolation Eric Gibbons, Ph.D.
University of Utah
Salt Lake City, UT, USA
09:40   Free-Breathing Cardiac MRI Using STORM & Deep-Learned Priors - Permission Withheld Sampurna Biswas, Ph.D. Candidate
University of Iowa
Iowa City, IA, USA
09:50 Autonomous CMR: Prescription to Ejection Fraction in Less Than 3 Minutes Okai Addy, Ph.D.
HeartVista, Inc.
Los Altos, CA, USA
10:00 Carotid Artery Wall Segmentation from Simultaneous Non-Contrast Angiography & intra-Plaque Hemorrhage (SNAP) Imaging Using U-Net Mingquan Lin, M.Sc.
City University of Hong Kong
Kowloon, Hong Kong
10:10 Deep Transfer Learning for PI-RADS Prediction from Multiparametric Prostate MR Imaging Studies Rebecca Mieloszyk, Ph.D.
University of Washington
Seattle, WA, USA
10:20 Will It Work in the Clinic? Considerations for the Validation of Artificial Intelligence in Medical Applications Tara Retson, M.D., Ph.D.
University of California, San Diego
La Jolla, CA, USA
10:30   Break & Speaker Upload Available
 
Session 9: Machine Learning for MRI: Broader Issues
  Moderators: Joseph Hajnal, Ph.D. & Lei (Leslie) Ying, Ph.D.
10:50 Encouraging Team Science for Machine Learning in Medical Imaging Roderic Pettigrew, M.D., Ph.D.
National Institutes of Health - NIBIB
Bethesda, MD, USA
11:10 Regulatory Strategies for Machine Learning-Based Medical Device Software Berkman Sahiner, Ph.D.
U.S. Food & Drug Administration
Washington, D.C., USA
11:30     Panel Discussion: Moving Forward, Recommendations, Study Group, & Plans
11:50   Best Papers & Poster Awards
12:00   Adjournment & Boxed Lunches
 
Back
The International Society for Magnetic Resonance in Medicine is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.