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Brain-Tumor-Detection-Model

A deep learning model for detecting brain tumors from MRI images using Convolutional Neural Networks (CNNs).

🧠 Brain Tumor Detection Model

This repository contains a trained deep learning model for detecting brain tumors from medical imaging data. The model is built using [TensorFlow/Keras] and saved in .h5 format (BTM.h5).

📂 Files

  • BTM.h5 – The pre-trained brain tumor detection model.

🚀 Model Overview

This model was developed as part of a research/academic project to classify brain MRI images into tumor vs. no-tumor categories. It is trained on a labeled dataset of MRI scans using a Convolutional Neural Network (CNN).

🧠 Model Architecture

  • Input Layer: 128x128 grayscale MRI images
  • Conv2D → ReLU → MaxPooling
  • Dropout for regularization
  • Fully Connected Dense Layers
  • Sigmoid / Softmax activation for binary/multi-class classification

📊 Dataset

The model was trained on a publicly available dataset of brain MRI images (e.g., from Kaggle) labeled with tumor presence. All images were preprocessed (resized, normalized) before training.