Automatic detection method of bladder tumor cells based on color and shape features  

作　　者：Zitong Zhao Yanbo Wang Jiaqi Chen Mingjia Wang Shulong Feng Jin Yang Nan Song Jinyu Wang Ci Sun 

机构地区：[1]Changchun Institute of Optics,Fine Mechanics and Physics Chinese Academy of Sciences,Changchun,Jilin 130033,P.R.China [2]University of Chinese Academy of Sciences,Beijing 100049,P.R.China [3]Bethune First Hospital of Jilin University:The First Hospital of Jilin University Changchun,Jilin 130061,P.R.China

出　　处：《Journal of Innovative Optical Health Sciences》2024年第6期1-13,共13页创新光学健康科学杂志（英文）

基　　金：Bethune Medical Engineering and Instrument Center Fund(E10133Y8H0);Jilin province science and technology development plan project(20210204216YY,20210204146YY).

摘　　要：Bladder urothelial carcinoma is the most common malignant tumor disease in urinary system,and its incidence rate ranks ninth in the world.In recent years,the continuous development of hyperspectral imaging technology has provided a new tool for the auxiliary diagnosis of bladder cancer.In this study,based on microscopic hyperspectral data,an automatic detection algorithm of bladder tumor cells combining color features and shape features is proposed.Support vector machine(SVM)is used to build classification models and compare the classification performance of spectral feature,spectral and shape fusion feature,and the fusion feature proposed in this paper on the same classifier.The results show that the sensitivity,specificity,and accuracy of our classification algorithm based on shape and color fusion features are 0.952,0.897,and 0.920,respectively,which are better than the classification algorithm only using spectral features.Therefore,this study can effectively extract the cell features of bladder urothelial carcinoma smear,thus achieving automatic,real-time,and noninvasive detection of bladder tumor cells,and then helping doctors improve the efficiency of pathological diagnosis of bladder urothelial cancer,and providing a reliable basis for doctors to choose treatment plans and judge the prognosis of the disease.

关 键 词：Bladder tumor cells microscopic hyperspectral fusion feature support vector machine automatic detection. 

分 类 号：R737.14[医药卫生—肿瘤]