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Variable resolution reconstruction for cartesian data acquired with nonconstant sampling density in phase‐encoding direction
Author(s) -
Rasche Volker,
Bornstedt Axel,
Hombach Vinzenz
Publication year - 2008
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.21538
Subject(s) - kernel (algebra) , aliasing , image resolution , sampling (signal processing) , iterative reconstruction , convolution (computer science) , image quality , undersampling , computer vision , computer science , cartesian coordinate system , resolution (logic) , encoding (memory) , upsampling , mathematics , artificial intelligence , algorithm , image (mathematics) , filter (signal processing) , geometry , combinatorics , artificial neural network
The variable‐kernel extent technique is applied for providing local high‐resolution images from k ‐space data sampled on a Cartesian sampling grid with gradually decreasing sampling density in the phase‐encoding direction. The approach is based on a variable spatial resolution reconstruction technique providing gradually decreasing resolution in the phase‐encoding direction with increasing distance to the image center, while preserving full spatial resolution in a narrow slab centered in spatial domain. Reconstruction is performed by a variable convolution kernel gridding technique. The convolution kernel width is chosen proportional to the k ‐space sampling spacing to utilize the respective apodization in the image for reduction of the aliasing artifacts. Application of this technique to carotid artery wall imaging shows the potential of the technique for a significant reduction of image acquisition time without sacrificing image quality in the region of the carotid arteries. Magn Reson Med 59:661–666, 2008. © 2008 Wiley‐Liss, Inc.