title: The research on medical image classification algorithm based on PLSA-BOW model.
abstract: 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.
authors.affiliation: College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, China.|Key Laboratory of Medical Image Computing of Ministry of Education, Northeastern University, Shenyang, Liaoning, China.|State Key Lab. for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China.
authors.forename: C H
authors.initials: CH
authors.lastname: Cao
authors.affiliation: College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, China.|Key Laboratory of Medical Image Computing of Ministry of Education, Northeastern University, Shenyang, Liaoning, China.|State Key Lab. for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China.
authors.forename: H L
authors.initials: HL
authors.lastname: Cao
mesh_terms: D000465:Algorithms; D003952:Diagnostic Imaging / Q000145:classification*; D006801:Humans; D008962:Models, Theoretical; D012106:Research; D012660:Semantics
keywords: Medical image classification; PLSA; bag of words model