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.

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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
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article

BRAIN TUMOR CLASSIFICATION FROM MRI IMAGES: A HYBRID APPROACH WITH PRE-PROCESSING AND FEATURE EXTRACTION

Satyam Singh, Parvin Mohane
American Journal of Management and IOT Medical Computing
Brain Tumor Detection and Classification
article

BRAIN TUMOR CLASSIFICATION FROM MRI IMAGES: A HYBRID APPROACH WITH PRE-PROCESSING AND FEATURE EXTRACTION

Satyam Singh, Parvin Mohane
article en

Abstract

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.

American Journal of Management and IOT Medical ComputingVol. 4(3)
Millennium Institute (BR), Millennium Engineering and Integration (United States) (US)
Openalex Percentile: Top 68%
Brain Tumor Detection and Classification
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