在基于图像的计算机辅助诊断中,综合考察目标形状与纹理将能获取更为全面的信息,使取得较高辅助诊断正确率成为可能。针对椎间盘退化在磁共振成像中体现出目标轮廓非刚体形变和区域灰度分布改变两大特征,提出分别量化刻画目标形状与纹理变化进而将其综合的思路,即首先采用测地线距离描述椎间盘轮廓非刚体形变程度,采用巴氏距离描述椎间盘区域灰度分布间的差异,进而将两种距离度量结合,通过无监督聚类方法将相似目标聚集,辅助医生有效地区分正常与退化的目标。实验中选取18人共108例腰椎间盘,来检验本文方法的准确度。实验结果表明,该方法结合形状与纹理的聚类准确率可达92.1%,高于单独使用形状或纹理时的准确率。

In image based computer aided diagnosis, higher accuracy can be achieved if the objects’ information of shape and texture can be used simultaneously. In spine MRI, intervertebral disc degeneration can be characterized by shape and texture variances. Therefore we propose a framework of computer aided diagnosis on disc degeneration as follows. First, we describe the disc degeneration by modeling non-rigid shape deformation and texture variance respectively. The deformation between the two shapes is measured by the geodesic length in the shape space. Similarly, the texture difference is measured by the Bhattacharyya distance between intensity distributions of two disc regions. Secondly, these two kinds of distances are added by weights as inputs of an unsupervised clustering machine. The clustering result is aimed at assisting doctors in distinguishing normal and degenerated intervertebral discs effectively. In experiments, 108 lumbar discs from 18 examinees are selected as experimental data. The highest accuracy of our proposed method is 92.1%, higher than the accuracy when shape or texture information is being used separately.