基于改进K-means算法的肠道肿瘤图像分析研究  

Image Inalysis of Intestinal Tumor Based on Improved K-means Algorithm

作　　者：杨波 张立娜[2] YANG Bo;ZHANG Li-na(Changchun University of Finance and Economics,Changchun 130122,China;Jilin Agricultural University,Changchun 130118,China)

机构地区：[1]长春财经学院信息工程学院,吉林长春130122 [2]吉林农业大学信息技术学院,吉林长春130118

出　　处：《电脑与信息技术》2021年第5期26-28,48,共4页Computer and Information Technology

基　　金：吉林省教育厅“十三五”科学技术重点项目(项目编号:JJKH20201256KJ)。

摘　　要：肠道肿瘤发病率近年来不断提高,医院门诊的就诊压力也在逐年增加,为缓解这一现象的出现,并且保证诊疗的准确性,文章采用改进的K-means算法进行肠道肿瘤图像分析。在人工诊疗的基础上,根据疾病和医学图像进行预测和建模,通过早期体检或专科疾病的检查,对患者肿瘤状况进行评估,在癌变前进行有针对性的干预。通过实验仿真,基于改进的K-means算法在样本数据上的应用效果良好,一定程度上提高了患者的就诊效率和诊断准确率。The incidence rate of intestinal tumor has been increasing in recent years.The pressure of outpatient service is increasing year by year.In order to alleviate this phenomenon and ensure the accuracy of diagnosis and treatment,K-means algorithm is used to analyze intestinal tumor images.On the basis of artificial diagnosis and treatment,according to the disease and medical image prediction and modeling,through early physical examination or specialized disease examination,the tumor status of patients is evaluated,and targeted intervention is carried out before cancelation.Through the experimental simulation,based on the improved k-means algorithm,the application effect on the sample data is good,and to a certain extent,the efficiency and accuracy of diagnosis are improved.

关 键 词：K-MEANS 机器学习 肠道肿瘤 图像分析 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]