The research on medical image classification algorithm based on PLSA-BOW model

作     者：Cao, C. H. Cao, H. L. 

作者机构：Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China Northeastern Univ Minist Educ Key Lab Med Image Comp Shenyang Liaoning Peoples R China Nanjing Univ State Key Lab Novel Software Technol Nanjing Jiangsu Peoples R China 

出 版 物：《TECHNOLOGY AND HEALTH CARE》 

年 卷 期：2016年第24卷第Suppl 2期

页      面：S665-S674页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 1204[管理学-公共管理] 1001[医学-基础医学(可授医学、理学学位)] 10[医学] 

主　　题：Medical image classification bag of words model PLSA 

摘      要：BACKGROUND: With the rapid development of modern medical imaging technology, medical image classification has become more important for medical diagnosis and treatment. OBJECTIVE: To solve the existence of polysemous words and synonyms problem, this study combines the word bag model with PLSA (Probabilistic Latent Semantic Analysis) and proposes the PLSA-BOW (Probabilistic Latent Semantic Analysis-Bag of Words) model. METHODS: In this paper we introduce the bag of words model in text field to image field, and build the model of visual bag of words model. RESULTS: The method enables the word bag model-based classification method to be further improved in accuracy. CONCLUSIONS: The experimental results show that the PLSA-BOW model for medical image classification can lead to a more accurate classification.