27th ISMRM Annual Meeting • 11-16 May 2019 • Montréal, QC, Canada

Sunrise Session
Advanced MSK MRI Acquisition & Post-Processing: Machine Learning

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Advanced MSK MRI Acquisition & Post-Processing: Machine Learning
Sunrise Session

ORGANIZERS: Jung-Ah Choi, Miika Nieminen, Edwin Oei, Jan Fritz

Monday, 13 May 2019
Room 516C-E  07:00 - 08:00 Moderators:  Victor Casula, Akshay Chaudhari

Skill Level: Intermediate to Advanced

Session Number: S-M-06

These four sessions will cover advanced MR imaging and MRI post-processing of the musculoskeletal system including machine learning, rapid imaging, fat suppression and quantification, and MR fingerprinting. Both a research and clinical perspective on each topic will be presented.

Target Audience
Scientists and clinicians interested in applying new MR or post-processing techniques for research or clinical applications.

Educational Objectives
As a result of attending this course, participants should be able to:
- Describe the advanced imaging or post-processing technique discussed in the session;
- Explain how the technique discussed has been applied in the musculoskeletal research; and
- Describe how the technique might be used clinically.



  Machine Learning: Research Perspective
Fang Liu
Musculoskeletal (MSK) imaging is a research field that remains lots of technical and clinical challenges. The recent development of Artificial Intelligence, particularly Deep Learning (DL), has demonstrated great potentials to resolve such challenges. This talk will present a technical overview of Deep Learning in MSK imaging and discuss some recent DL applications that successfully translate new learning-based approaches into performance improvement in MSK imaging workflow.  One major aim is to draw tightly connections between fundamental DL concepts and technical challenges in MSK imaging. Topics will cover from rapid image acquisition, reconstruction, and MR parameter mapping, to image post-processing such as image segmentation and translation in MSK imaging. The talk will conclude with a discussion of open problems in DL that are particularly relevant to MSK imaging and the potential challenges and opportunities in this emerging field.

  Machine Learning: Clinical Perspective
Richard Kijowski
There has been much interest in the use of deep learning in medical imaging.  While recent surveys on deep learning in medical imaging have shown a wide variety of applications in all imaging subspecialties, applications in musculoskeletal imaging have remained relatively limited.  This talk will review the current uses of deep learning in musculoskeletal imaging including tissue segmentation, image reconstruction, and disease detection.

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