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.