Brain Tumor Detection from MRI Using Deep Learning and Genetic Algorithm
This paper explores the methodology for the implementation of a brain tumor detection tool that uses the advantages of the deep learning strategy and also, in addition, the genetic algorithm is used for the optimization of the detection model. The model works by taking a large amount of brain MRI images and perform training using both the CNN and the Genetic algorithm to predict the results. There are several pre-processing steps are done on the MRI input images. Optimizing using the genetic algorithm makes the model more accurate in predictions. It also helps the healthcare organizations to aware about the brain tumors and more fast and reliable they can figure out. The strategy used can extensively enhance the general overall performance of the brain tumor detection from the MRI images and offering a scalable and adaptable solution that may be carried out in the real time. The model can also be used for certain other medical conditions.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-08-27
- DOI
- https://doi.org/10.5281/zenodo.16961124
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00