PURPOSE: To evaluate three-dimensional nonlinear anisotropic filtering in suppressing image noise in high spatial resolution magnetic resonance angiograms (MRA) acquired with hybrid undersampled projection reconstruction and phase contrast vastly undersampled isotropic projection reconstruction (PC-VIPR). MATERIALS AND METHODS: Three-dimensional nonlinear anisotropic filtering was quantitatively analyzed and evaluated through the measurement of contrast to noise ratio (CNR) in PC-VIPR images and contrast enhanced peripheral MRA images. To filter MRA images with ultra-high spatial resolution and poor CNR, a spatial frequency dependent nonlinear anisotropic filtering algorithm was proposed that uses two-step processing to filter the whole spatial frequency data. RESULTS: Three-dimensional nonlinear anisotropic filtering was shown to be effective in suppressing noise and improving CNR in MRA with isotropic spatial resolution. Higher CNR was achieved using spatial frequency dependent nonlinear anisotropic filtering. A typical CNR gain of between 50-100% was shown in our studies. CONCLUSION: Three-dimensional nonlinear anisotropic filtering significantly improved CNR in MRA images with isotropic spatial resolution. Spatial frequency dependent nonlinear anisotropic filtering further improved CNR for MRA images with ultra-high spatial resolution and low CNR. Copyright 2004 Wiley-Liss, Inc.
PURPOSE: To evaluate three-dimensional nonlinear anisotropic filtering in suppressing image noise in high spatial resolution magnetic resonance angiograms (MRA) acquired with hybrid undersampled projection reconstruction and phase contrast vastly undersampled isotropic projection reconstruction (PC-VIPR). MATERIALS AND METHODS: Three-dimensional nonlinear anisotropic filtering was quantitatively analyzed and evaluated through the measurement of contrast to noise ratio (CNR) in PC-VIPR images and contrast enhanced peripheral MRA images. To filter MRA images with ultra-high spatial resolution and poor CNR, a spatial frequency dependent nonlinear anisotropic filtering algorithm was proposed that uses two-step processing to filter the whole spatial frequency data. RESULTS: Three-dimensional nonlinear anisotropic filtering was shown to be effective in suppressing noise and improving CNR in MRA with isotropic spatial resolution. Higher CNR was achieved using spatial frequency dependent nonlinear anisotropic filtering. A typical CNR gain of between 50-100% was shown in our studies. CONCLUSION: Three-dimensional nonlinear anisotropic filtering significantly improved CNR in MRA images with isotropic spatial resolution. Spatial frequency dependent nonlinear anisotropic filtering further improved CNR for MRA images with ultra-high spatial resolution and low CNR. Copyright 2004 Wiley-Liss, Inc.
Authors: Erik T Bieging; Alex Frydrychowicz; Andrew Wentland; Benjamin R Landgraf; Kevin M Johnson; Oliver Wieben; Christopher J François Journal: J Magn Reson Imaging Date: 2011-03 Impact factor: 4.813
Authors: A S Turk; K M Johnson; D Lum; D Niemann; B Aagaard-Kienitz; D Consigny; J Grinde; P Turski; V Haughton; C Mistretta Journal: AJNR Am J Neuroradiol Date: 2007-01 Impact factor: 3.825