Performance Evaluation of Content Based Image Retrieval for Medical Images

Abstract

Content-based image retrieval (CBIR) technology benefits not only large image collections management, but also helps clinical care, biomedical research, and education. Digital images are found in X-Rays, MRI, CT which are used for diagnosing and planning treatment schedules. Thus, visual information management is challenging as the data quantity available is huge. Currently, available medical databases utilization is limited image retrieval issues. Archived digital medical images retrieval is always challenging and this is being researched more as images are of great importance in patient diagnosis, therapy, medical reference, and medical training. In this paper, an image matching scheme using Discrete Sine Transform for relevant feature extraction is presented. The efficiency of different algorithm for classifying the features to retrieve medical images is investigated.

Extracted Key Phrases

2 Figures and Tables

Cite this paper

@inproceedings{Kumar2013PerformanceEO, title={Performance Evaluation of Content Based Image Retrieval for Medical Images}, author={Sasi Kumar and Y. S. Kumaraswamy}, year={2013} }