Local shape 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 an enhancement of signal-to-noise ratio in magnetic resonance imaging without degradation of resolution. Instead of conventional template filtering where template shape is fixed, multiple templates are defined in the proposed method and optimal template among the multiple templates is selected and applied in pixel-by-pixel basis. By the proposed scheme, edge blurring is minimized by selecting mostly matched template, yet SNR enhancement by the filtering is fully utilized. Compared to existing two-dimensional linear least square error filter or direction-adaptive recursive filter, the proposed shape-adaptive filter with multiple templates provides higher SNR and sharper edges for both natural images and artificial resolution phantom images.