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

被引：9
|
作者：
Cao, C. H. [1 ,2 ,3 ]
Cao, H. L. [1 ,2 ,3 ]
机构：
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China
[2] Northeastern Univ, Minist Educ, Key Lab Med Image Comp, Shenyang, Liaoning, Peoples R China
[3] Nanjing Univ, State Key Lab Novel Software Technol, Nanjing, Jiangsu, Peoples R China
来源：
TECHNOLOGY AND HEALTH CARE | 2016年 / 24卷
关键词：
Medical image classification; bag of words model; PLSA;
D O I：
10.3233/THC-161194
中图分类号：
R19 [保健组织与事业（卫生事业管理）];
学科分类号：
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.
引用
收藏
页码：S665 / S674
页数：10
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