Abstract:

In order to meet the requirement of medical image auxiliary diagnosis, we present a feature fusion algorithm based on Apriori algorithm: texture features and patient natural features in HIS(Hospital Information System). Accordingly, the combination of pruning methods associated rule base, prototype system for a CT(Computer Tomography) image is divided into normal and abnormal categories. Experiments were evaluated in accordance with the system, showing that association rules established by the algorithm library, in the auxiliary doctor diagnosed, with good results.

Key words: Apriori algorithm, texture features, CT(Computer Tomography) Images, association rules, classification