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Medical image disease classification method based on naive Bayes

A medical imaging and disease classification technology, applied in the field of medical imaging disease classification, can solve the problems of inconvenient scientific research and retrieval by doctors, and the inability to classify medical imaging inspection reports in time, achieving good results, improving completeness, and ensuring accuracy

Inactive Publication Date: 2014-07-30
HANGZHOU DIANZI UNIV +1
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Problems solved by technology

[0007] Aiming at the problem that medical image inspection reports cannot be classified in time, which brings a lot of inconvenience to doctors' scientific research retrieval, using the advantages of simple Bayesian algorithm, high efficiency, strong stability and good accuracy, the present invention proposes a A naive Bayesian-based medical imaging disease classification method to solve the above technical problems

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  • Medical image disease classification method based on naive Bayes
  • Medical image disease classification method based on naive Bayes
  • Medical image disease classification method based on naive Bayes

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[0035] In order to make the technical means and creative features of the present invention easy to understand, the following describes the implementation of the present invention in further detail with reference to the accompanying drawings and examples.

[0036] Such as figure 1 As shown, the Naive Bayes-based medical imaging disease classification method provided by the present invention specifically includes the following steps:

[0037] Step 1: First use the k-means algorithm to perform disease cluster analysis, and divide the disease types into ten categories. With the help of the international disease type classification standard ICD-10, these ten categories are identified and coded; for example, the disease types are classified as follows and coded:

[0038] Tumor (C00-D48)

[0039] Circulatory system diseases (I00-I99)

[0040] Respiratory system disease (J00-J99)

[0041] Digestive system diseases (K00-K93)

[0042] Musculoskeletal system and connective tissue diseases (M00-M9...

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Abstract

The invention discloses a medical image disease classification method based on naive Bayes. According to an equipment type and image finding, diagnosis and other text information in a diagnosis report form, the disease type which an image examination result belongs to is automatically judged. Considering the influence of the independence assumption of naive Bayes classification in actual application, the method carries out disease clustering analysis by utilizing a K-Means clustering algorithm, data with the high similarity level are classified into the same cluster, data with the low similarity level are classified into different clusters, and meanwhile the number of disease categories is determined. The characteristics of high efficiency and high speed of a naive Bayes algorithm are utilized, classification precision is guaranteed, and meanwhile classification speed of medical image search is improved to a large degree.

Description

Technical field [0001] The invention relates to the field of medical imaging disease classification, in particular to a method for medical imaging disease classification based on Naive Bayes. Background technique [0002] With the construction of digital hospitals, large hospitals have accumulated a large amount of medical text information for many years. In the face of this vast amount of text data, how to quickly search and find useful information, use these texts from multiple angles, and effectively classify and sort this information Therefore, it is especially urgent to dig out hidden and useful medical knowledge and experience. Therefore, it is very important to study automatic classification and clustering techniques to improve traditional database structured queries. [0003] Text classification and clustering is an important branch in the field of text information processing. Its goal is to study how to organize and manage text information more effectively, and quickly, a...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
Inventor 徐哲洪嘉鸣霍洪波何必仕
Owner HANGZHOU DIANZI UNIV
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