ISMRM 25th Annual Meeting & Exhibition • 22-27 April 2017 • Honolulu, HI, USA

Sunrise Educational Session: It Doesn’t Have to Be That Way: Information & Diagnosis
Sunrise Session

ORGANIZERS: Michael S. Hansen, Ph.D. & Joshua D. Trzasko, Ph.D.

Wednesday, 26 April 2017
Room 315  07:00 - 07:50 Moderators: Michael Hansen, Sebastian Kozerke

Skill Level: Intermediate

Slack Channel: #e_crosscutting
Session Number: SW04

Most clinical MRI is performed using slightly variations of standard technology. However, in the research domain, many groups are now pushing the limits of what MRI technology can do, identifying new realms that it can be applied to, and violating the classic dogmas to enable wholly new imaging capabilities. In this course, we will explore some of these MRI technology extremes, investigate their technical foundations, and identify what potential impact they could have on clinical practice.

Target Audience
Physicists and Engineers who are interested in pushing the limits of MRI technology and exploring non-traditional uses of the latter.

Educational Objectives
Upon completion of this course, participants should be able to:

-Identify and describe MRI techniques that employ non-traditional hardware setups (e.g., magnets, gradients);
-Identify and describe MRI techniques that employ non-traditional data acquisition strategies (e.g., RF, sampling); and
-Identify and describe MRI techniques that employ non-traditional data processing strategies (e.g., artifact-to-information, assisted diagnosis).

Artifact to Information using Structured Low Rank Matrix Completion
Jong Chul Ye
MRI artifacts arise from various sources, including instability of an MR system, patient movement, inhomogeneities of gradient fields,  etc. Such MRI artifacts are generally considered as irreversible so that additional artifact-free scan or navigator scan is required. To overcome these limitations, this paper discusses the physical origin of various MR artifacts and novel compressed sensing-based approaches for removing these MRI artifacts.

Computer Assisted Diagnosis
Alistair Young
Artificial intelligence (AI) and machine learning (ML) are advancing rapidly, as evidenced by the recent success of AI systems in the automated diagnosis of cancerous skin lesions from images or autism from brain MRI. This talk will give course participants an overview of current capability and future applications in the fields of image interpretation, classification and analysis.


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.