Automated tongue segmentation in hyperspectral images for medicine.
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.
Liu
Zhi
Z
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China.
Yan
Jing-qi
JQ
Zhang
David
D
Li
Qing-Li
QL
D001185:Artificial Intelligence; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007091:Image Processing, Computer-Assisted; D010363:Pattern Recognition, Automated / Q000379:methods*; D012107:Research Design; D012680:Sensitivity and Specificity; D013053:Spectrophotometry / Q000295:instrumentation / Q000379:methods*; D014059:Tongue / Q000033:anatomy & histology*