RECOGNITION OF MAGNETIC RESONANCE IMAGES USING INTELLIGENT SYSTEMS

Akhmedova Zukhra Khalipaevna, Gadzhiev Amir Malikovich, Medzhidov Zaur Urudzhalievich, Gadzhiev Malik Amirovich

Currently, the creation of tools and intelligent platforms for the use of resting-state functional magnetic resonance imaging (fMRI) in surgery is a relevant area of research. These tools can significantly improve the accuracy and efficiency of surgical planning, reduce resource costs and improve clinical practice. Examples of such developments are computer vision systems for automatic image segmentation, neural network models for pathology classification and generative models for synthesizing new data. The use of these technologies in medicine has great potential for improving the quality of life of patients and increasing the efficiency of healthcare. The purpose of the work is to study modern information technologies using artificial intelligence systems for recognizing magnetic resonance imaging of the brain. The results of the work include the developed intelligent program, as well as a comparative analysis of decoding images of magnetic resonance imaging of the brain.

Keywords:image recognition, functional magnetic resonance imaging of the brain, intelligent systems, neural networks, image segmentation, computer vision.