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

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.

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