基于稀疏分解的医学CT图像去噪

医学CT图像成像过程中,由于成像机制的影响,不可避免的引入噪声。图像中的噪声会降低图像质量,影响临床诊断。因此,有必要对医学CT图像进行去噪处理。本文采用图像的稀疏分解方法来对混有噪声的肝癌CT图像进行消噪处理,提出分块稀疏分解去噪。实验表明,本文算法对医学图像中噪声去除有一定效果。在分解原子个数相同的条件下,本文方法去噪后重建图像比在整幅图像上进行稀疏去噪重建的计算速度提高了约15倍。

Denoising of medical CT image based on sparse decomposition

Noises are inevitably introduced to medical CT images because of various factors in the medical image processes. Noises in medical images will greatly degrade the quality of images and bring difficulties to clinical diagnosis. Therefore, it is necessary for medical CT images to be denoised. In the present paper, the sparse decomposition of images is used to denoise medical CT images. A new block-based sparse decomposition of images denoising method is proposed. Experimental results showed that block-based sparse decomposition of images denoising had a certain function. With the same number of atoms, the computing speed of the image constructed by the new algorithm was improved by about 15 times, compared with the whole image sparse decomposition denoising.