摘要
新疆地方性肝包虫病是新疆牧区发病率较高的传染性寄生虫病,严重影响牧区各族人民的身体健康。根据图像特征,选择合适距离算法,实现快速准确的图像检索,对辅助医生早期发现、诊断和治疗肝包虫病有重大意义。文章研究比较了使用肝包虫病医学图像纹理特征进行图像检索时,不同距离算法的有效性。实验结果表明:对于肝包虫病医学图像的基于灰度共生矩阵(GLCM)的纹理特征图像检索,马氏距离算法优于其他距离算法。
Xinjiang local liver hydatid disease is an infectious parasitic disease in Xinjiang pastoral areas. Based on the image features, selecting the appropriate distance algorithms to retrieve the image quickly and accurately, different distance algorithms have been induced in this area, which can greatly assist the doctors to early detect, diagnose and cure the liver hydatid disease. This paper compared the performance of different distance algorithms to retrieve the image when using the liver hydatid disease medical image texture features. The results showed that： for the liver hy- datid disease medical images retrieval based on gray level cocurrence matrix （GLCM） texture features, the Mahal- anobis distance algorithm is superior to other distance algorithms.
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2013年第5期942-945,共4页
Journal of Biomedical Engineering
基金
国家自然科学基金资助项目(30960097
81160182)
关键词
肝包虫
图像检索
灰度共生矩阵
纹理特征
Liver hydatid
Image retrieval
Gray level concurrence matrix （GLCM）
Texture feature
