ISMRM22 - Acquisition & Analysis in Context: Body MRI Image Acquisition & Reconstruction

Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting • 07-12 May 2022 • London, UK

Acquisition & Analysis in Context: Body MRI Image Acquisition & Reconstruction

Sunrise Course

ORGANIZERS: Andrew Scott, Fang Liu, Mark Chiew, Khin Tha, Janine Lupo, Dan Ma, Brian Hargreaves

Monday, 09 May 2022

ICC Capital Suite 14-16

08:00 - 09:00

Moderators: Alexey Samsonov

Skill Level: Basic to Intermediate

Session Number: S-M-06

Session Number: S-M-06

Overview
Junior Fellow Observer: Bragi Sveinsson

While many MR data acquisition and image analysis techniques are broadly applicable, there are often strong context-specific strategies that take into account the particular constraints, challenges, and opportunities that are unique to different clinical or physical contexts. This course will first review acquisition and analysis methods for clinical neuroimaging, followed by musculoskeletal imaging, and body imaging. A final session on acquisition and analysis in the context of different field strengths will be presented.

Target Audience
Clinicians, scientists, engineers, technologists, and other professionals interested in learning about acquisition and analysis techniques in different contexts.

Educational Objectives
As a result of attending this course, participants should be able to:
- Outline data acquisition and analysis methods used for clinical neuroimaging;
- Summarize the methods available for musculoskeletal imaging;
- Describe the acquisition and analysis strategies used in body imaging;
- Compare and contrast the advantages and disadvantages of ultra-high and low field MRI; and
- Recognize the differences in MR techniques used in different clinical and physical contexts.

	08:00		Picking the Right Tool for the Right Job: Body MRI Sequences View the Presentation Ali Syed
	08:30		Picking the Right Tool for the Right Job: Cardiovascular MRI Analysis Techniques View the Presentation Albert Hsiao We will present techniques for analysis of cardiovascular MR imaging, principally addressing how we are applying deep learning to address acquisition, analysis and interpretation.