The research on medical image classification algorithm based on PLSA-BOW model
Chunhong Cao, H.L. Cao · Technology and Health Care · 2016
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.