An Improved Level Set Method for Vertebra CT Image Segmentation
Background: Clinical diagnose and therapy for the lumbar disc herniation requires accurate vertebra segmentation.The complex anatomical structure and the degenerative deformations of the vertebra makes its segmentation challenging.Methods: In this paper, an improved level set method, namely edge-and region-based level set method (ERBLS), is proposed for vertebral CT images segmentation.By considering the gradient information and local region characteristics of images, the proposed model can efficiently segment images with intensity inhomogeneity and blur or discontinuous boundaries.To reduce the dependency on manual initialization in many active contour models and for an automatic segmentation, a simple initialization method for the level set function is built, which utilizes the optimal threshold obtained automatically by Otsu algorithm.In addition, the need of the costly re-initialization procedure is completely eliminated.Results: Experimental results on both synthetic and real images demonstrated that the proposed ERBLS model is very robust and efficient.Compared with the well-known local binary fitting (LBF) model, our method is much more computationally efficient and much less sensitive to the initial contour.The proposed method has also applied to 56 patient data sets and produced very promising results.Conclusions: In this paper, an improved level set method suitable for vertebra CT images is proposed.It has the flexibility of segmenting the vertebra CT images with blur or discontinuous edges, internal inhomogeneity and no need of re-initialization.
Level set method Image segmentation Vertebral CT images
Juying Huang Fengzeng Jian Haiyun Li
Computer Simulation and Medical Imaging Laboratory, College of Biomedical Engineering, Capital Medic Department of Neurosurgery, Xuanwu Hospital Affiliated to Capital Medical University, Beijing, China
国内会议
北京
英文
164-178
2012-12-01（万方平台首次上网日期，不代表论文的发表时间）