Brain Tumor Detection

Medical Image Classification using CNN

Project Overview

  • Enhanced a deep learning model for accurate classification of MRI scans as Tumor and Non-Tumor detections.
  • Preprocessing methods were conducted, including resizing, normalization, and transformation from RGB images to grayscale, to improve data quality.
  • Developed a deep learning (CNN) architecture for the classification using labeled datasets and verified performance of the model using accuracy & F1-score measures.
  • Heatmapped and plotted the classification metrics of the predictions to reorient them and infer medical decisions.
  • Tech Stack: Python, TensorFlow, OpenCV, NumPy, Matplotlib

Project Visuals

MRI Scan Classification Interface

A screenshot of the application interface for classifying MRI scans.

CNN Model Architecture Diagram

A diagram illustrating the CNN architecture used in the project.