Document Type
Article
Disciplines
1.2 COMPUTER AND INFORMATION SCIENCE, Computer Sciences, 3. MEDICAL AND HEALTH SCIENCES
Abstract
The brain is one of the most important and complex organs in the body, consisting of billions of individual cells. Uncontrolled growth and expansion of aberrant cell populations within or around the brain are the main causes of brain tumors. These cells have the potential to harm healthy cells and impair brain function [1]. Tumors can be detected using medical imaging techniques, which are considered the most popular and accurate way to classify different types of cancer, and this procedure is even more crucial as it is noninvasive [2]. Magnetic resonance imaging (MRI) is one such medical imaging technique that has proven particularly useful in classifying different types of brain cancer due to its ability to provide high-resolution images of brain tissue.
DOI
https://doi.org/10.1109/ACCESS.2023.3281546
Recommended Citation
Ganesh, Narayanan; Jayalakshmi, Sambandan; Chandran Narayanan, Rama; Mahdal, Miroslav; Zawbaa, Hossam; and Mohamed, Ali Wagdy, "Gated Deep Reinforcement Learning With Red Deer Optimization for Medical Image Classification" (2023). Articles. 205.
https://arrow.tudublin.ie/scschcomart/205
Funder
Ministry of Education, Youth and Sports, Czech Republic, through the Application of Machine and Process Control Methods (Grant No. SP2023/074)
Creative Commons License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 International License.
Included in
Computer Engineering Commons, Electrical and Computer Engineering Commons, Medicine and Health Sciences Commons
Publication Details
https://ieeexplore.ieee.org/document/10145063
N. Ganesh, S. Jayalakshmi, R. C. Narayanan, M. Mahdal, H. M. Zawbaa and A. W. Mohamed, "Gated Deep Reinforcement Learning With Red Deer Optimization for Medical Image Classification," in IEEE Access, vol. 11, pp. 58982-58993, 2023, doi: 10.1109/ACCESS.2023.3281546.
DOI: 10.1109/ACCESS.2023.3281546