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Abstract #2746

Improving DESS contrast in 7T hip images using L1-norm denoising and optimal echo combination

Aurelien Destruel1, Mingyan Li 1, Craig Engstrom2, Ewald Weber1, Jin Jin1,3,4, Rahel Heule5, Oliver Bieri6, Feng Liu1, and Stuart Crozier1
1School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia, 2School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, Australia, 3University of Southern California, Los Angeles, CA, United States, 4Siemens Healthcare Pty Ltd, Brisbane, Australia, 5High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 6Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland

The double-echo steady-state (DESS) sequence has been used successfully in 3T MRI imaging of the musculoskeletal system for segmentation of joint. However, in 3D-DESS images acquired at 7T MRI, a reduction in the contrast between tissues due to an increased diffusion sensitivity may complicate cartilage segmentation. Typically, the signals acquired with DESS are averaged without any pre-processing. However, these signals give different contrasts and have different noise behaviours. In this work, we improve the contrast-to-noise ratio (CNR) whilst preserving anatomical detail in high-resolution 7T DESS images through a new approach combining L1-norm denoising and p-norm combination of the echo signals.

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