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
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
In this work, we improve the contrast-to-noise ratio (CNR) whilst
preserving anatomical detail in high-resolution 7T DESS images of the hip joint through a new
approach combining L1-norm denoising and p-norm combination of the two DESS signals (PSIF and FISP).
Figure 5: Comparison between (top) the original DESS,
(centre) norm-optimized DESS and (bottom) denoised norm-optimized DESS images in
three planes. The white arrows show the synovial fluid, the blue arrows show
the ligaments.
Figure 2: SI images of PSIF, FISP and DESS with and without L1-norm
denoising. Sequence parameters were: resolution = 0.4x0.4x0.6mm3, field-of-view = 155x155mm2,
matrix = 384x384, TE/TR = 4.12/14.8ms, bandwidth = 250Hz, flip angle = 20°, TA = 6min06sec