Brain Tumor MRI Dataset (Glioma, Meningioma, Pituitary, No Tumor)

Published: 11 September 2025| Version 1 | DOI: 10.17632/zwr4ntf94j.1
Contributors:
MD IRFANUL KABIR HIRA,
,

Description

This dataset contains 12,064 pre-processed T1-weighted contrast-enhanced MRI brain images, categorized into four classes: Glioma, Meningioma, Pituitary, and No Tumor. The dataset is split into 80% training data and 20% testing data. Images are organized into subfolders by class. It is suitable for machine learning and deep learning research in brain tumor classification, tumor detection, and computer-aided diagnosis.

Files

Steps to reproduce

This dataset contains 12,064 T1-weighted contrast-enhanced brain MRI images, categorized into four classes: (1) Glioma Tumor (2) Meningioma Tumor (3) Pituitary Tumor (4) No Tumor (Normal) The dataset is organized into 80% training data and 20% testing data, making it suitable for machine learning and deep learning research in tumor detection and classification. ๐Ÿ“Š Dataset Composition: Training Data (80%) Glioma: 3,018 images Pituitary: 2,504 images Meningioma: 2,183 images No Tumor: 1,945 images Testing Data (20%) Glioma: 755 images Pituitary: 546 images Meningioma: 626 images No Tumor: 487 images ๐Ÿ“‚ Folder Structure: /Brain_Tumor_MRI_Dataset/ โ”œโ”€โ”€ train/ โ”‚ โ”œโ”€โ”€ Glioma/ โ”‚ โ”œโ”€โ”€ Meningioma/ โ”‚ โ”œโ”€โ”€ Pituitary/ โ”‚ โ””โ”€โ”€ No_Tumor/ โ”œโ”€โ”€ test/ โ”‚ โ”œโ”€โ”€ Glioma/ โ”‚ โ”œโ”€โ”€ Meningioma/ โ”‚ โ”œโ”€โ”€ Pituitary/ โ”‚ โ””โ”€โ”€ No_Tumor/ ๐Ÿ“ท Image Details: Format: JPEG/PNG Modality: T1-weighted contrast-enhanced MRI Color: Grayscale or RGB (depending on scan) Pre-processed and organized into labeled folders ๐Ÿงช Applications: Brain tumor classification Deep learning (CNN, transfer learning) Computer-aided diagnosis (CAD) Radiology research and teaching ๐Ÿ”’ Licensing: This dataset is shared under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Users may share and adapt the dataset with proper citation. ๐Ÿ“ฌ Contact: For questions or collaboration: Md Irfanul Kabir Hira email: erfanulkabirhira132@gmail.com Department of Computer Science and Engineering My Files : Upload your zipped folders (train.zip and test.zip) or the raw directory structure.

Institutions

  • National Institute of Textile Engineering and Research
  • Dhaka University of Engineering and Technology

Categories

Computer Science, Radiology, Health Sciences, Artificial Intelligence, Computer Vision, Medical Imaging, Magnetic Resonance Imaging, Tumor, Machine Learning, Meningioma, Brain Tumor, Glioma, Pituitary Tumor, Deep Learning

Licence