May 15, 2019

MONTREAL - While most of the focus on machine learning in radiology has been image interpretation, Jong Chul Ye, PhD, of the Korea Advanced Institute of Science and Technology (KAIST) in South Korea believes that data reconstruction is also a fertile area for deep learning. He explains in this video from the International Society for Magnetic Resonance in Medicine (ISMRM) conference.

Video loading ...
Jong Chul Ye, PhD, of KAIST.

Video from ISMRM 2019: Tal Arbel on machine learning and image analysis
MONTREAL - Machine learning in MRI was the focus of Tuesday's plenary session at the International Society for Magnetic Resonance in Medicine (ISMRM)....
Video from ISMRM 2019: Dr. Bradley Erickson on machine learning and clinical MRI
MONTREAL - Machine learning in MRI was the focus of Tuesday's plenary session at the International Society for Magnetic Resonance in Medicine (ISMRM)....
Video from ISMRM 2019: Dr. Hedvig Hricak on disruptors in MRI interpretation
MONTREAL - Monday morning's talks on disruptors in MRI came to a close with a talk on disruption in the interpretation of MRI data by Dr. Hedvig...
Video from ISMRM 2019: Mark Griswold on disruptors in MRI visualization
MONTREAL - Disruptors in MRI was the topic of the Monday morning sessions at the International Society for Magnetic Resonance in Medicine (ISMRM) meeting...
Video from ISMRM 2019: Dr. Daniel Sodickson on MRI disruptors
MONTREAL - What disruptive forces are changing radiology in general and MRI in particular? Dr. Daniel Sodickson, PhD, of New York University School...

Copyright © 2019 AuntMinnie.com

Last Updated bc 5/14/2019 8:52:20 PM