Liu Zhi, Yan Jing-qi, Zhang David, Li Qing-Li
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China.
Appl Opt. 2007 Dec 1;46(34):8328-34. doi: 10.1364/ao.46.008328.
Automatic tongue area segmentation is crucial for computer aided tongue diagnosis, but traditional intensity-based segmentation methods that make use of monochromatic images cannot provide accurate and robust results. We propose a novel tongue segmentation method that uses hyperspectral images and the support vector machine. This method combines spatial and spectral information to analyze the medical tongue image and can provide much better tongue segmentation results. The promising experimental results and quantitative evaluations demonstrate that our method can provide much better performance than the traditional method.
自动舌区分割对于计算机辅助舌诊至关重要，但利用单色图像的传统基于强度的分割方法无法提供准确且稳健的结果。我们提出了一种使用高光谱图像和支持向量机的新型舌分割方法。该方法结合空间和光谱信息来分析医学舌图像，并且能够提供更好的舌分割结果。有前景的实验结果和定量评估表明，我们的方法比传统方法具有更好的性能。
