Anisotropic anomalous diffusion filtering applied to relaxation time estimation in magnetic resonance imaging

Relaxometry mapping is a quantitative modality in magnetic resonance imaging (MRI) widely used in neuroscience studies. Despite its relevance and utility, voxel measurement of relaxation time in relaxometry MRI is compromised by noise that is inherent to MRI modality and acquisition hardware. In order to enhance signal to noise ratio (SNR) and quality of relaxometry mapping we propose application of anisotropic anomalous diffusion (AAD) filter that is consistent with inhomogeneous complex media. Here we evaluated AAD filter in comparison to two usual spatial filters: Gaussian and non local means (NLM) filters applied to real and simulated T2 relaxometry image sequences. The results demonstrate that AAD filter is comparatively more efficient in noise reducing and maintaining the image structural edges. AAD shows to be a robust and reliable spatial filter for brain image relaxometry.