Hands-on Tutorial: Laying the Foundations of Cardiovascular MRI Reconstruction
Sunrise Course
ORGANIZERS: Teresa Correia, Christopher Nguyen, Tobias Wech
Tuesday, 13 May 2025
316B
07:00 -
08:00
Moderators: Noriko Oyama-Manabe & Maarten Terpstra
Skill Level: Basic to Intermediate
Session Number: S-T-02
No CME/CE Credit
Session Number: S-T-02
Overview
This hands-on tutorial will provide practical guidelines on how to perform compressed sensing and AI-based reconstructions from accelerated cardiovascular MRI acquisitions. This session is part of a series of 3 weekday lectures (1 weekday session, 2 hours) with 3 hands-on sunrise sessions (3 x 1 hour) to provide practical demonstrations of key concepts of cardiovascular MRI, including 1) clinical protocols for identifying cardiovascular disease, 2) accelerated acquisition strategies and corresponding reconstruction techniques, 3) automated post-processing and reporting workflows. This tutorial will also introduce the building blocks of machine learning and provide practical examples of how these are used in cardiovascular MRI.
Weekday lectures:
1. Acquisition: Protocols and Planning I (35min)
2. Reconstruction: Faster and Better scans I (35min)
3. Post-processing & Analysis: Faster and Automated workflows I (35min)
4. Panel discussion (15min)
Sunrise sessions:
1. Acquisition: Protocols and Planning II (60min)
2. Reconstruction: Faster and Better scans II (60min)
3. Post-processing & Analysis: Faster and Automated workflows II (60min)
Target Audience
This tutorial is for physicians, radiographers, physicists, and engineers who want to learn about accelerated cardiovascular MRI image reconstruction methods. It is suitable for beginners and also for those who want to brush up on their knowledge or explore advanced topics in cardiovascular MRI.
Educational Objectives
As a result of attending this course, participants should be able to:
• Summarize rapid acquisition strategies and corresponding reconstruction techniques for CMR;
• Demonstrate how to design code for compressed sensing image reconstruction; and
• Demonstrate how to design code for AI-based image reconstruction.
| 07:00 | | Introduction Teo Lynette |
| 07:30 | | Reconstruction: Faster & Better Scans II Thomas Küstner |