Carballido-Gamio Julio, Belongie Serge J, Majumdar Sharmila
Joint Graduate Group in Bioengineering, University of California, San Francisco, 94143-1290, USA.
IEEE Trans Med Imaging. 2004 Jan;23(1):36-44. doi: 10.1109/TMI.2003.819929.
Segmentation of medical images has become an indispensable process to perform quantitative analysis of images of human organs and their functions. Normalized Cuts (NCut) is a spectral graph theoretic method that readily admits combinations of different features for image segmentation. The computational demand imposed by NCut has been successfully alleviated with the Nyström approximation method for applications different than medical imaging. In this paper we discuss the application of NCut with the Nyström approximation method to segment vertebral bodies from sagittal T1-weighted magnetic resonance images of the spine. The magnetic resonance images were preprocessed by the anisotropic diffusion algorithm, and three-dimensional local histograms of brightness was chosen as the segmentation feature. Results of the segmentation as well as limitations and challenges in this area are presented.
医学图像分割已成为对人体器官及其功能图像进行定量分析不可或缺的过程。归一化割（NCut）是一种光谱图论方法，很容易接受不同特征的组合用于图像分割。对于不同于医学成像的应用，通过奈斯特罗姆近似方法已成功缓解了NCut所带来的计算需求。在本文中，我们讨论了将NCut与奈斯特罗姆近似方法应用于从脊柱矢状面T1加权磁共振图像中分割椎体。磁共振图像通过各向异性扩散算法进行预处理，并选择亮度的三维局部直方图作为分割特征。本文给出了分割结果以及该领域的局限性和挑战。
