Three-dimensional Adaptive Filtering in Magnetic Resonance Angiography

C.-F. Westin, L. Wigström, T. Loock, L. Sjökvist, R. Kikinis, H. Knutsson
Journal of Magnetic Resonance Imaging
Volume 14, Pages 63-71
2001

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Abstract

In order to enhance 3D image data from magnetic resonance angiography (MRA), a novel method based on the theory of multidimensional adaptive filtering has been developed. The purpose of the technique is to suppress image noise while enhancing important structures. The method is based on local structure estimation using six 3D orientation selective filters, followed by an adaptive filtering step controlled by the local structure information. The complete filtering procedure requires approximately 3 minutes of computational time on a standard workstation for a 256x256x64 data set. The method has been evaluated using a mathematical vessel model and in vivo MRA data (both phase contrast and time of flight (TOF)). 3D adaptive filtering results in a better delineation of small blood vessels and efficiently reduces the high-frequency noise. Depending on the data acquisition and the original data type, contrast-to-noise ratio (CNR) improvements of up to 179 (8.9 dB) were observed. 3D adaptive filtering may provide an alternative to prolonging the scan time or using contrast agents in MRA when the CNR is low.

Index terms: angiography; adaptive filtering; noise reduction; tensor; image enhancement

MIPs of TOF MRA data before (a) and after (b) adaptive filtering.

Reference

Westin CF, Wigström L, Loock T, Sjökvist L, Kikinis R, Knutsson H. Three-dimensional adaptive filtering in magnetic resonance angiography. Journal of Magnetic Resonance Imaging 2001;14:63-71.

Bibtex entry

@Article{westinJMRI01,
  author         = {C.-F. Westin and L. Wigstr{\"o}m and T. Loock and L.       
                   Sj{\"o}kvist and R. Kikinis and H. Knutsson},               
  title          = {Three-dimensional Adaptive Filtering in Magnetic Resonance 
                   Angiography},                                               
  journal        = {Journal of Magnetic Resonance Imaging},                    
  year           = 2001,                                                       
  volume         = {14},                                                       
  pages          = {63--71}
}

Grants

NIH P41-RR13218 (NAC), CIMIT

Research areas

Vessles, Tensor, Adaptive Filtering

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