关键词: 非局部均值方法（NLM）, 高斯滤波, 动脉自旋标记（ASL）, 图像去噪

Abstract: Arterial Spin Labeling（ASL） MR images suffer from low SNR. In order to achieve adequate high image quality, it is necessary to execute experiment a number of times repeatedly. 3D Gaussian filter is widely in clinical use but the filter effect is not good enough. A new ASL image denoising algorithm based on Non-Local Means（NLM） denoising method is proposed. The new denoising method uses region similarity weight to decrease SNR and increases the accuracy of Cerebral Blood Flow（CBF） map. The results of CBF maps indicate that the CBF map obtained by the proposed method is more close to the real result than the Gaussian smoothing, which realizes the goal of obtaining accurate CBF map in the case of less repeated times.

Key words: Non-Local Means（NLM）, Gaussian filtering, Arterial Spin Labeling（ASL）, image denoising