Abstract
The article substantiates the feasibility and practical value of using a specific simulation modeling methodology, which provides for digital processing and the mathematical essence of neural network technology. A brain tumor is a serious disease, and the number of people who die due to a brain tumor, despite significant progress in treatment remains impressive. In this research presents in detail the developed algorithm for high-performance identification of objects (early detection and identification of tumors) on MRI images by geometric features. This algorithm, based on image pre-processing, analyzes the data array using a convolutional neural network (CNN) and recognizes pathologies in the images. The obtained algorithm is a step towards the creation of autonomous automatic identification and decision-making systems for the diagnosis of malignant tumors and other neoplasms in the brain by geometric features.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
