Deep learning based brain tumor detection

By MarksMaster
Deep Learning, Deep Learning Projects in Python, Machine Learning, Image Processing, Artificial Intelligence Deep Learning
Intermediate, Expert, Bachelors/Undergraduate, Masters/Postgraduate

The project involves designing and implementing a deep learning-based brain tumor detection system using MRI images. The goal is to determine whether a person has a brain tumor by analyzing their brain MRI image. This system is crucial for the early detection of brain tumors, which is difficult for doctors to achieve manually. Here's a summarized breakdown of your project:

  • Objective: Create a deep learning-based system for brain tumor detection using MRI images to detect brain tumors at an early stage.
  • Technology Stack:
    • Frameworks: TensorFlow and AutoKeras for model development.
    • Libraries: OpenCV for image processing.
    • Web Framework: Flask for building the deployment application.
  • Data:
    • Dataset: 3000 MRI images, split equally between tumor-containing and tumor-free images.
  • Model Development:
    • Architecture: AutoKeras helps determine optimal model parameters using AutoML.
    • Training: Train the model on the provided dataset to predict the presence of a brain tumor.
  • Deployment:
    • Flask Application: Create a user-friendly web application for model deployment.
    • Model Loading: Load the trained model into memory at application startup.
  • User Interaction:
    • Web Interface: Users access the application via a browser.
    • Image Upload: Users can upload their brain MRI images for analysis.
  • Prediction and Visualization:
    • Image Processing: Uploaded images are resized using OpenCV to match model input dimensions.
    • Prediction: The loaded model processes the image and predicts tumor presence with associated probabilities.
    • Result Display: The application's result page shows the user's uploaded image, predicted label (tumorous or non-tumorous), and the associated probability.
  • Tumor Detection Outcome:
    • Early Detection: The system's early detection capability helps address the challenge of identifying brain tumors in their early stages.
  • Additional Feature:
    • Healthcare Center Recommendations: If the image is predicted as tumorous, the application provides a list of top US healthcare centers for brain diagnosis.

Overall, project leverages deep learning, automated model architecture search, and web application development to create a powerful tool for early brain tumor detection using MRI images. The integrated system offers both accurate predictions and practical support for users seeking medical assistance.

Project Comes with Report,code,webapp,and ppt

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