Decision tree based medical image clustering algorithm in computer-aided diagnoses

Article type: Research Article

Authors: Zhou, Wei^* | Wang, Hongqiang | Yang, Chunmei | Bai, Yang | Wang, Dongliang | Zhan, Yongfeng

Affiliations: General Hospital of Shenyang Military Region, Shenyang, Liaoning, China

Correspondence: [*] Corresponding author: Wei Zhou, General Hospital of Shenyang Military Region, Shenyang, Liaoning, China. Tel.: +86 24 2889 7203; E-mail:zweitgzy@126.com

Abstract: With the rapid development of intelligent diagnostic medical imaging, artificial intelligent methods have become a research hotspot in this field with the rapid development of medical imaging intelligent diagnosis. The new research progress of artificial intelligence in medical image processing in recent five years is discussed. This paper discussed the function of medical image mining in computer-aided diagnoses. The idea of using luminance grade as the features of CT image and the method of extracting and storing the luminance grade are proposed. The results of classification based on decision tree and clustering based on density to some brain and breast CT images and the analysis to them are introduced. Moreover, the conclusion and future work are given.

Keywords: Image mining, diagnoses support, luminance grade, decision tree

DOI: 10.3233/JCM-150585

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 15, no. 4, pp. 645-651, 2015