Variable resolution reconstruction for cartesian data acquired with nonconstant sampling density in phase‐encoding direction

Abstract

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.