摘要
为了解决在图像中检测和定位人体膝关节前交叉韧带的问题,促进前交叉韧带重建手术的研究,提出一种基于分层检测的前交叉韧带定位方法.该方法将韧带定位分为全局与局部检测;根据不同的样例图像选择不同的图像特征;基于随机森林构建对应的全局和局部检测器,通过确定膝关节中前交叉韧带的整体组织的位置,再进一步识别属于前交叉韧带的具体区域,从而实现对它的准确定位.基于真实人体膝关节MRI图像的实验结果表明,文中方法对前交叉韧带检测的识别能力高,且定位准确.
In order to address the problem of detecting and locating the anterior cruciate ligament of human＇s knee in medical image and promote the study of its reconstruction operation, this paper proposes a hierarchical detection based method to locate the anterior cruciate ligament. The location task is performed in the global and the local detections successively. The features are selected according to the type of image samples, and the corresponding global and local detectors are built based on the random forests respectively to first find the entire region of the anterior cruciate ligament and then recognize its definite area. Experimental results based on the real MRI images validate the effectiveness and accuracy of our method.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2013年第12期1862-1867,共6页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(40672203)
西南交通大学博士创新基金
关键词
分层检测
韧带定位
随机森林
hierarchical detection
ligament location
random forests
