BRAIN TUMOR CLASSIFICATION FROM MRI IMAGES: A HYBRID APPROACH WITH PRE-PROCESSING AND FEATURE EXTRACTION
A brain tumor is an abnormal growth of cells within the brain that can disrupt its normal functions. Early detection is vital, as tumors can become cancerous. MRI and CT scans are commonly used for diagnosis, allowing timely treatment. This research aims to identify and locate brain tumors using MRI images through a three-step process: pre-processing, segmentation, and classification. Pre-processing involves converting images to grayscale and removing noise. Segmentation then isolates the tumor region, and feature extraction highlights key attributes for accurate classification.
Authors
- Satyam Singh
- Parvin Mohane
Institutions
- Millennium Institute (BR)
- Millennium Engineering and Integration (United States) (US)
Publication Details
- Journal
- American Journal of Management and IOT Medical Computing
- Published
- 2025-09-19
- DOI
- https://doi.org/10.64751/ajmimc.2025.v4.n3.pp65-69
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00