Brain Tumor Segmentation and Classification in MRI

This project demonstrates a MATLAB-based approach for brain tumor detection and classification using MRI images.
The algorithm applies morphological operations, thresholding, and radial distance analysis to segment the tumor region and classify it as Benign or Malignant based on boundary variance.

Features

• Brain extraction from MRI scans using morphological processing.\
• Tumor segmentation with adaptive thresholding.\
• Feature extraction based on radial distance variance.\
• Tumor classification into:
  • Benign
  • Malignant\
• Visual outputs including:
  • Original MRI image\
  • Segmented tumor mask\
  • Highlighted tumor region\
  • Radial distance signature plot

Output Example

Here is some examples of the program output:

Dataset

The MRI images used for this project were taken from the Kaggle Brain MRI Images Dataset.
(dataset_Kaggle)

Important Note

This project is purely academic and experimental.
It is not a reliable medical diagnostic tool and should not be used for real clinical decisions.
Results depend heavily on image quality and preprocessing.

---

Author: Shady Nikooei
Field: Digital Image Processing