Earticle

초록

영어

The MR image has provided lots of information used for medical examination. Accurate and robust brain MR image segmentation, feature extraction and feature classification are very important for clinical tumor diagnosis. A new tumor diagnosis method based on brain MR images is hereby put forward. Firstly, detect the deformed area of the images through multi-threshold segmentation morphology, and then, extract the GMM feature used for the classification, and finally, classify the types of tumor images by using decision tree classifier. The whole classification consists of two stages, during training stage extract the different features of tumor images and non-tumor images, and during testing stage conduct the classification of tumor and non-tumor based on knowledge databank. The computing method is appraised according to the three performance index including accuracy, false alarm rate and loss detecting rate, the experiment results show that the computing function is excellent and is helpful for better brain tumor diagnosis.

목차

Abstract
 1. Introduction
 2. This Article’s Methods
  2.1. Multi-Threshold Segmentation
  2.2. GMM Feature Extraction
  2.3. Decision Tree Classifier
 3. Experiment Result and Analysis
 4. Conclusion
 Acknowledgement
 References

키워드

저자

• Yang Li [ Department of Basic Public, WanNan Medical College, Wuhu Anhui 241002, China ]
• Ye Mingquan [ Department of Basic Public, WanNan Medical College, Wuhu Anhui 241002, China ]
• Zhang Hao [ Department of Basic Public, WanNan Medical College, Wuhu Anhui 241002, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605