Analysis of human brain by magnetic resonance imaging using content-based image retrieval - Rizvi, Qaim Mehdi (International Journal of Health Sciences, 2020)
Objective: Content-based image retrieval (CBIR) is the most suitable and alternative method for older text searches that use keywords. This article aims to improve feature extraction as well as matching techniques designed for more accurate and precise CBIR systems, especially for brain scan images associated with various brain diseases and abnormalities. Tests should be described at an appropriate success rate. Methods: Various methods of producing medical images are discussed, and examples of biological applications are given. The discussion emphasizes as an introduction to CBIR the new method of echo-planar imaging, which is fully described. We have done here many methods related to digital image processing and we had developed a code for retrieving everything automatically. This application has been developed in Matlab software. Results: Testing the correctness and effectiveness of the system evolved becomes more important when the system is going to be used in real-time and more when it is for humankind, i.e., medical diagnosis. Nowadays, our science and technology areas as develop as we can say that we have such advanced medical equipment so that our thought and program can be capable that it is giving us useful results. Determining if whether the two images are identical or not, it depends on the point of view of the person. Conclusions: In this paper, the outcome of feature extraction and matching by setting cutoff limit and threshold is pretty promising. Further studies can be done apart from computed tomography scans for a more generalized CBIR system.