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 Jin^1,3,4, 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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