Intensity-curvature functional-based filtering in image space and k-space: Applications in magnetic resonance imaging of the human brain

Abstract

This research examines the use of the intensity-curvature functional (ICF) as filter in image space and in k-space. The novelty of this study is three-folded: (a) The evidence that the ICF calculated from three additional (International Journal of Imaging Systems and Technology, 28, 2018, 54) two-dimensional model polynomial functions is an image space filter; (b) An additional (The use of the intensity-curvature functional as k-space filter: Applications in magnetic resonance imaging of the human brain, 2018) ICF-based k-space filtering technique applicable to two-dimensional magnetic resonance images; (c) Results obtained through the calculation of the ICF of the trivariate cubic Lagrange model polynomial function (LGR3D). Although ICF-based k-space filtering delivers clear and well-defined images, ICF-based image space filtering remains superior when reconstructing vessel images in T2 MRI. The ICF of the LGR3D function provides sharp images too.