---
license: cc0-1.0
tags:
- BrainTumor
models:
- AIOmarRehan/Brain_Tumor_Classification_with_Grad-CAM
configs:
- config_name: default
  data_files:
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': glioma
          '1': meningioma
          '2': notumor
          '3': pituitary
  splits:
  - name: test
    num_bytes: 23698544
    num_examples: 1311
  download_size: 25969079
  dataset_size: 23698544
---

# Brain Tumor MRI Dataset

## Overview
This dataset contains **7,023 human brain MRI images** organized into **four categories**:  

- Glioma  
- Meningioma  
- Pituitary  
- No Tumor  

It is designed for research in **brain tumor detection and classification** using deep learning methods. The dataset is a combination of three sources: **Figshare**, **SARTAJ**, and **Br35H**. Note that the "No Tumor" class images were sourced from the Br35H dataset.

---

## Motivation
Early and accurate detection of brain tumors is critical for treatment planning and patient survival. Automated classification using deep learning, particularly **Convolutional Neural Networks (CNNs)**, can assist in identifying tumor type, location, and malignancy grade, helping medical professionals make informed decisions faster.

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## Dataset Details
- **Total images:** 7,023  
- **Classes:** Glioma, Meningioma, Pituitary, No Tumor  
- **Image format:** MRI scans  
- **Preprocessing:** Image sizes vary; resizing and margin removal are recommended before training.  

> Note: Some glioma images in the original SARTAJ dataset were incorrectly labeled. Those images have been replaced with correct ones from Figshare.

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## Recommended Usage
- **Classification tasks:** Predict tumor type (glioma, meningioma, pituitary, no tumor).  
- **Segmentation tasks:** Identify tumor location within the brain MRI.  
- **Multi-task models:** Detect, classify, and locate tumors using a single CNN-based model.

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## Citation & Feedback
If you use this dataset, please consider citing it or giving feedback. Your suggestions and comments are welcome and help improve future versions.

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## License
[CC0: Public Domain](https://creativecommons.org/publicdomain/zero/1.0/)