Noise Removal of MRI Data with Edge Enhancing
Yan Lin Xu, Minxiong Zhou, Ling Xu, Wei Liu, Guang Yang · 2011
Magnetic Resonance Imaging (MRI) data always suffer from noise, especially for fast scanning sequence, such as EPI sequence which is basis for Functional MRI. Thus smoothing or denoising methods are always applied to suppress noise, but unavoidably blurs fine anatomical structure. While detail enhancement of denoised images is desirable, it often comes with kinds of artifacts. In this paper, a new strategy was proposed to combine image denoising and Multi-scale contrast enhancing techniques. The procedure extracted a continuous and noise resistant edge from original image first, and then used it to combining the denoised image and High Frequency Components from Laplacian Pyramid technique. The algorithm was tested with both synthetic and real data, the experimental results showed that it smoothed image in homogeneous regions while preserved or enhanced details and edges of anatomical structure without introducing evident artifacts.)