CLASSIFICATION OF BIOMEDICAL IMAGES USING CONTENT BASED IMAGE RETRIEVAL SYSTEMS

Authors

  • Yinghui Zhang University of California, Berkeley, USA
  • Fengyuan Zhang Northeastern University, China
  • Yantong Cui Anshan No.1 High School, China
  • Ruoci Ning Marian High School, USA

DOI:

https://doi.org/10.29121/ijetmr.v5.i2.2018.161

Keywords:

Biomedical Images, Content-Based Image Retrieval (CBIR), Gray-Level Co-Occurrence Matrix

Abstract

Because of the numerous application of Content-based image retrieval (CBIR) system in various areas, it has always remained a topic of keen interest by the researchers. Fetching of the most similar image from the complete repository by comparing it to the input image in the minimum span of time is the main task of the CBIR. The purpose of the CBIR can vary from different types of requirements like a diagnosis of the illness by the physician, crime investigation, product recommendation by the e-commerce companies, etc. In the present work, CBIR is used for finding the similar patients having Breast cancer. Gray-Level Co-Occurrence Matrix along with histogram and correlation coefficient is used for creating CBIR system. Comparing the images of the area of interest of a present patient with the complete series of the image of a past patient can help in early diagnosis of the disease. CBIR is so much effective that even when the symptoms are not shown by the body the disease can be diagnosed from the sample images.

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Published

2018-02-28

How to Cite

Zhang, Y., Zhang, F., Cui, Y., & Ning, R. (2018). CLASSIFICATION OF BIOMEDICAL IMAGES USING CONTENT BASED IMAGE RETRIEVAL SYSTEMS. International Journal of Engineering Technologies and Management Research, 5(2), 181–189. https://doi.org/10.29121/ijetmr.v5.i2.2018.161