Brain Tumor Detection in Magnetic Resonance Images Using Genetic Algorithms With Multiple Stages

DOI

10.2991/978-94-6463-716-8_58How to use a DOI?

Keywords

Genetic optimization; MRI; GLCM; brain tumor; SURF; advanced machine learning

Abstract

Biomedicine is still attempting to overcome one of the profession’s most pressing problems: detecting brain tumors. Early detection of brain cancer is possible with advanced technology or instruments. Classifying brain cancer types utilizing patent brain images allows for automation in automated operations. Furthermore, the proposed new method is used to distinguish between brain tumors and other brain illnesses. To distinguish the cancer from the other parts of the brain, the input image is first pre-processed. Following that, the images are separated into different hues and levels before being processed using the Grey Level Co-Occurrence and SURF extraction methods to reveal crucial information in the photos. Genetic optimization reduces the size of the retrieved attributes. An advanced learning technique is utilized to train and validate tumor categorization based on cut-down characteristics. The technique’s accuracy, error, sensitivity, and specificity are all compared to the present method. The approach has a 90% + accuracy rate, with less than 2% inaccuracy for all types of cancer. Finally, the specificity and sensitivity are greater than 89% and 91%, respectively. Genetic algorithms are more efficient because the methods used are more accurate and specialized than the other ways.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Ajay Vyas
AU  - Vaishali Poriya
AU  - Sandeep Mathariya
AU  - Nilesh Jain
AU  - Mahaveer Jain
PY  - 2025
DA  - 2025/05/26
TI  - Brain Tumor Detection in Magnetic Resonance Images Using Genetic Algorithms With Multiple Stages
BT  - Proceedings of the International Conference on Recent Advancements and Modernisations in Sustainable Intelligent Technologies and Applications (RAMSITA 2025)
PB  - Atlantis Press
SP  - 789
EP  - 802
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-716-8_58
DO  - 10.2991/978-94-6463-716-8_58
ID  - Vyas2025
ER  -