结合图像增强的心血管内超声中-外膜边缘检测

针对心血管内超声(IVUS)图像中-外膜边缘检测中,伪影、斑块及血管分支等造成边缘难以准确检测的问题,提出一种基于空频域图像增强的中-外膜边缘检测算法。首先,采用一种空频域相结合的增强算法对图像进行增强处理,该增强算法结合了基于方向滤波器组的频率域增强算法与基于邻域、直方图均衡化的空间域增强算法的优点,同时克服了前者导致的对比度降低的缺陷及后者带来的图像细节模糊的缺陷。然后,将增强后的图像数据矩阵作为代价矩阵,利用启发式图搜索法对代价矩阵进行图搜索,从而获取中-外膜边缘。实验结果表明,本文增强算法在增强中-外膜边缘特征的同时改善了图像的对比度和清晰度,使基于其增强结果的图搜索能准确地检测到中-外膜边缘,其检测正确率达到92.76%,提高了IVUS图像中-外膜边缘检测的准确性。

Image enhancement based media-adventitia border detection in intravascular ultrasound images

An important challenge in the analysis of intravascular ultrasound images (IVUS) is the media-adventitia border detection. However, as a result of the inevitable artifact, plaque and imaging equipment effect, the target border always appears too fuzzy to be detected. In this paper, a new border detection method based on spatial-frequency domain image enhancement is proposed. The method uses enhancing processes in the spatial and xin the frequency domain during the detecting process. In the enhancing process, the directional filter band, neighborhood and histogram equalization are combined to overcome the defect of contrast reduction caused by directional filter and the defect of details vagueness caused by histogram equalization. Then in the detecting process, a heuristic graph-searching is applied to find the media-adventitia border by taking the enhanced image data matrix as the cost matrix. The experiment results show that the enhancing process not only strengthens the features of the media and adventitia greatly, but also improves the contrast and definition of the image. The graph-searching based on the enhanced results can detect the media-adventitia border accurately.The correct rate reached 92.76%.