Optimization of 4D flow MRI velocity field in the aorta with divergence-free smoothing
暂无分享,去创建一个
Shihua Zhao | Xingli Liu | Wei Wang | Runjie Wei | Mansu Jin | Hongping Wang | Qi Gao | Peng Wu | Zhaozhuo Niu | Fei Li | Shihua Zhao | Runjie Wei | Hongping Wang | Peng Wu | Q. Gao | Wei Wang | Xingli Liu | Fei Li | Zhaozhuo Niu | Mansu Jin | R. Wei
[1] P. J. Gamez-Montero,et al. ESTIMATION OF WALL SHEAR STRESS USING 4D FLOW CARDIOVASCULAR MRI AND COMPUTATIONAL FLUID DYNAMICS , 2017 .
[2] M. Markl,et al. 4D flow MRI, cardiac function, and T1‐mapping: Association of valve‐mediated changes in aortic hemodynamics with left ventricular remodeling , 2018, Journal of magnetic resonance imaging : JMRI.
[3] F. Bolster,et al. Association of variant arch anatomy with type B aortic dissection and hemodynamic mechanisms , 2017, Journal of vascular surgery.
[4] J. Westerweel,et al. Universal outlier detection for PIV data , 2005 .
[5] H. Marquering,et al. The Effect of Spatial and Temporal Resolution of Cine Phase Contrast MRI on Wall Shear Stress and Oscillatory Shear Index Assessment , 2016, PloS one.
[6] Kevin M. Johnson,et al. Aortic flow patterns and wall shear stress maps by 4D-flow cardiovascular magnetic resonance in the assessment of aortic dilatation in bicuspid aortic valve disease , 2018, Journal of Cardiovascular Magnetic Resonance.
[7] S. Grieve,et al. 4D flow magnetic resonance imaging: role in pediatric congenital heart disease , 2018, Asian cardiovascular & thoracic annals.
[8] B. S. Manjunath,et al. Multisensor Image Fusion Using the Wavelet Transform , 1995, CVGIP Graph. Model. Image Process..
[9] D. Gallo,et al. On the Use of In Vivo Measured Flow Rates as Boundary Conditions for Image-Based Hemodynamic Models of the Human Aorta: Implications for Indicators of Abnormal Flow , 2012, Annals of Biomedical Engineering.
[10] N J Pelc,et al. Noise reduction in three‐dimensional phase‐contrast MR velocity measurementsl , 1993, Journal of magnetic resonance imaging : JMRI.
[11] K. Ho-Shon,et al. A comparison of 4D flow MRI-derived wall shear stress with computational fluid dynamics methods for intracranial aneurysms and carotid bifurcations - A review. , 2018, Magnetic resonance imaging.
[12] Damien Garcia,et al. Robust smoothing of gridded data in one and higher dimensions with missing values , 2010, Comput. Stat. Data Anal..
[13] Jinjun Wang,et al. Divergence-free smoothing for volumetric PIV data , 2016 .
[14] A. Kendall,et al. A method for estimating wall friction in turbulent wall-bounded flows , 2008 .
[15] Hao Liu,et al. Blood flow dynamic improvement with aneurysm repair detected by a patient-specific model of multiple aortic aneurysms , 2014, Heart and Vessels.
[16] Kevin M Johnson,et al. In vivo three‐dimensional MR wall shear stress estimation in ascending aortic dilatation , 2011, Journal of magnetic resonance imaging : JMRI.
[17] Sebastian Kozerke,et al. Reconstruction of divergence‐free velocity fields from cine 3D phase‐contrast flow measurements , 2013, Magnetic resonance in medicine.
[18] Matts Karlsson,et al. WALL SHEAR STRESS IN A SUBJECT SPECIFIC HUMAN AORTA - INFLUENCE OF FLUID-STRUCTURE INTERACTION , 2011 .
[19] S. Oyre,et al. Accurate noninvasive quantitation of blood flow, cross-sectional lumen vessel area and wall shear stress by three-dimensional paraboloid modeling of magnetic resonance imaging velocity data. , 1998, Journal of the American College of Cardiology.
[20] Yasuo Takehara,et al. Validation of numerical simulation methods in aortic arch using 4D Flow MRI , 2017, Heart and Vessels.
[21] Michael Markl,et al. Interdependencies of aortic arch secondary flow patterns, geometry, and age analysed by 4-dimensional phase contrast magnetic resonance imaging at 3 Tesla , 2012, European Radiology.
[22] Guang-Zhong Yang,et al. Helical and Retrograde Secondary Flow Patterns in the Aortic Arch Studied by Three‐Directional Magnetic Resonance Velocity Mapping , 1993, Circulation.
[23] Petter Dyverfeldt,et al. 4D flow MRI can detect subtle right ventricular dysfunction in primary left ventricular disease , 2016, Journal of magnetic resonance imaging : JMRI.
[24] Michael Markl,et al. 4D flow MRI , 2012, Journal of magnetic resonance imaging : JMRI.
[25] M. Markl,et al. Aortic Valve Stenosis Alters Expression of Regional Aortic Wall Shear Stress: New Insights From a 4‐Dimensional Flow Magnetic Resonance Imaging Study of 571 Subjects , 2017, Journal of the American Heart Association.
[26] G. Yin,et al. Contributing Factor of Proximal Arch Dilation in Patients with Bicuspid Aortic Valve-Wall Shear Stress or Upward Extension of Ascending Aorta Dilation? , 2020, The heart surgery forum.
[27] H. Marquering,et al. Volumetric arterial wall shear stress calculation based on cine phase contrast MRI , 2015, Journal of magnetic resonance imaging : JMRI.
[28] Y. Takehara,et al. Characterizing saccular aortic arch aneurysms from the geometry‐flow dynamics relationship , 2017, The Journal of thoracic and cardiovascular surgery.
[29] H. Kooijman,et al. 4D flow cardiovascular magnetic resonance for monitoring of aortic valve repair in bicuspid aortic valve disease , 2020, Journal of Cardiovascular Magnetic Resonance.
[30] Alastair J. Martin,et al. Phase‐contrast magnetic resonance imaging measurements in intracranial aneurysms in vivo of flow patterns, velocity fields, and wall shear stress: Comparison with computational fluid dynamics , 2009, Magnetic resonance in medicine.
[31] Thomas S. Huang,et al. A fast two-dimensional median filtering algorithm , 1979 .
[32] Nurettin Özgür Doğan,et al. Bland-Altman analysis: A paradigm to understand correlation and agreement , 2018, Turkish journal of emergency medicine.
[33] J. Hennig,et al. Quantitative 2D and 3D phase contrast MRI: Optimized analysis of blood flow and vessel wall parameters , 2008, Magnetic resonance in medicine.
[34] M. Markl,et al. The Role of Imaging of Flow Patterns by 4D Flow MRI in Aortic Stenosis. , 2019, JACC. Cardiovascular imaging.
[35] Ulrich Rist,et al. Spatial resolution enhancement/smoothing of stereo–particle-image-velocimetry data using proper-orthogonal-decomposition–based and Kriging interpolation methods , 2007 .
[36] N. Otsu. A threshold selection method from gray level histograms , 1979 .