Adaptive template filtering for signal-to-noise ratio enhancement in magnetic resonance imaging

In this paper, a local shape-adaptive template filtering is proposed for the enhancement of the signal-to-noise ratio (SNR) without the loss of resolution in magnetic resonance (MR) imaging. Unlike conventional filtering, where the template shape and coefficients are fixed, multiple templates are defined in the proposed algorithm. An optimal template is selected and optimal filtering, based on the template, is applied on a pixel-by-pixel basis. Using the proposed process, edge blurring is minimized and SNR enhancement is maximized by selecting the optimally matched template. Compared to existing two-dimensional (2-D) adaptive linear least square error (LLSE) filters or direction-adaptive recursive filters, the proposed adaptive template filter provides higher SNR and sharper edges for both MR and artificial resolution phantom images.