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Abstract #2667

Streaming-MoCo: Real-Time Motion-Compensated Image Reconstruction from 3D Non-Cartesian MRI

Fatih Calakli1,2 and Simon K Warfield1,2
1Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, United States, 2Department of Radiology, Harvard Medical School, Boston, MA, United States

Synopsis

Keywords: Motion Correction, Brain, streaming, motion correction, real-time, image reconstruction, 3D, radial, non-cartesian

Motivation: A real-time motion compensation monitoring system is vital for structural MRI:

  • to assess the effectiveness of motion correction even during k-space data collection,
  • to ensure the rapid delivery of corrected images afterwards.

Goal(s): Develop a system that enables real-time:

  1. motion-compensation,
  2. image reconstruction,
  3. and visualization,
during k-space data collection.

Approach: Introduced a framework that includes online:

  1. coil compression,
  2. rigid motion-tracking,
  3. motion-compensated gridding,
  4. image generation/streaming.
Tested it at 3T by imaging two volunteers with:
  1. no motion,
  2. instructed motion.

Results: Streaming motion-compensated image reconstructions from 3D radial MRI and the progression of image quality improvements were demonstrated in real-time during k-space data collection.

Impact: Our streaming-MoCo framework enables rapid reconstruction of motion-compensated images both during k-space data collection and post scan. This facilitates immediate assessment of image quality during scans, and potentially trigger corrective action well in advance before the scan concludes.

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Abstract

Keywords