Abstract
BackgroundClinical diagnosis and therapy for the lumbar disc herniation requires accurate vertebra segmentation. The complex anatomical structure and the degenerative deformations of the vertebrae makes its segmentation challenging.MethodsAn improved level set method, namely edge- and region-based level set method (ERBLS), is proposed for vertebra 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 blurry 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 Otsu threshold. In addition, the need of the costly re-initialization procedure is completely eliminated.ResultsExperimental 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.ConclusionsAn improved level set method suitable for vertebra CT images segmentation is proposed. It has the flexibility of segmenting the vertebra CT images with blurry or discontinuous edges, internal inhomogeneity and no need of re-initialization.
Highlights
Clinical diagnosis and therapy for the lumbar disc herniation requires accurate vertebra segmentation
We are sure that accurate 2D vertebra segmentation will help us reconstruct 3D vertebra geometric model because 3D vertebra segmentation modeling is fundamentally performed based on a set of axial slices
Active shape models (ASMs) [4] was a kind of Statistical shape models (SSMs) that iteratively searched a boundary while maintaining shape constraints
Summary
Clinical diagnosis and therapy for the lumbar disc herniation requires accurate vertebra segmentation. The understanding of geometrical information about the normal anatomy and the degenerative bony deformations of the spine necessitates vertebra CT image segmentation for the clinical diagnosis and the preoperative planning of spinal diseases. Active appearance models (AAMs) [5] which combined appearance information and shape constraints, could provide better robust results than ASMs in many medical segmentation applications. Klinder T [12] first used various kinds of models, such as shape, gradient, and appearance information, and applied 3D deformable model approach to segment the vertebra CT images. The framework incorporated prior shape knowledge through the KDE and local geometrical features by introducing Willmore flow into the level set segmentation and obtained good 3D segmentation results of normal spinal vertebra images
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
