中文摘要：

血管内超声（IVUS）图像的分割对于动脉粥样硬化疾病的研究和介入治疗具有重要的意义，但由于其自身存在斑点噪声，从而严重影响图像自动分割的准确性和速度。提出一种基于Contourlet变换和非线性扩散的斑点去除算法（CTND）；利用自适应的对比度因子，在Contourlet域直接对IVUS图像各方向子带进行非线性扩散滤波，而不需要同态处理。实验结果表明，这种算法在保持IVUS图像强、弱边缘的同时，能有效地去除斑点噪声，并为图像外膜的提取奠定良好的基础。

英文摘要：

The segmentation of intravascular ultrasound arteriosclerosis disease and intervention therapy. However, （IVUS） images has great significance in the study of due to its inherent speckle noise, the speed and accuracy of automatic segmentation of IVUS images would be influenced severely. In this paper, a novel speckle reduction algorithm based on contourlet transform and nonlinear diffusion （CTND） was proposed. Using the adaptive contrast factor, the directional subbands of IVUS image were fihered by nonlinear diffusion without a homomorphic operation in contourlet domain. Experimental results showed that the algorithm could effectively reduce the speckle noise while preserving the strong and weak edges for IVUS images, laying a good foundation for the detection of the adventitia of IVUS images.