以腹膜接种人胃癌细胞SGC-7901的裸鼠为胃癌腹膜播散的动物模型，进行模拟外科手术，在体探测不同种植期的裸鼠腹膜癌结节及正常腹膜组织的激光拉曼光谱，对比光谱差异，采用支持向量机(SVM)算法对光谱进行分类和分期判决。结果表明，癌结节和正常组织拉曼光谱差异显著，用支持向量机算法进行分类的灵敏度、特异度和诊断准确度分别为95.73%、70.73%和90.73%；不同生长期的癌结节组织拉曼光谱也存在明显差异，用支持向量机算法进行分期的结果分别为98.82%、98.73%和98.78%。从分类结果可以看出，此方法对指导外科手术中癌变组织的识别有重要的意义。

The nude mice injected with human gastric cancer cells (SGC-7901) in their peritoneums are chosen as animal models of gastric cancer peritoneal dissemination in this research. The Raman spectra at 785 nm excitation of both these nude mice which are in different tumor planting periods and the normal counterpart are taken in vivo in the imitate laparotomy. 205 spectra are collected. The spectra of different tissue types are compared and classified by support vector machine (SVM) algorithm. The results show significant differences between normal and malignant tissues. For normal and malignant tissues, the sensitivity, specificity and accuracy are 95.73%, 70.73% and 90.73%, respectively, while for different tumor planting periods, they are 98.82%, 98.73% and 98.78%. The experimental results show that Raman spectra differ significantly between cancerous and normal gastric tissues, which provides experimental basis for the diagnosis of gastric cancer by Raman spectroscopy technology. And SVM algorithm can give well generalized classification performance for the samples, which expands the application of mathematical algorithms in classification.