Hugging Face's logo

Datasets:
melisklc0
/
stroke-classification

Tasks:
Image Classification
Modalities:
Image
Languages:
English
Tags:
medical
stroke
ct-scan
data-augmentation
License:
Dataset card Data Studio Files
xet
 Community
stroke-classification / README.md
melisklc0's picture
melisklc0
Create README.md
c0935f8 verified
preview code
|
raw
history blame contribute delete
3.34 kB
metadata 
license: cc-by-4.0
task_categories:
  - image-classification
tags:
  - medical
  - stroke
  - ct-scan
  - data-augmentation
language:
  - en
pretty_name: Stroke Classification Dataset (CT Scans)

🧠 Stroke Classification CT Scans Dataset

Dataset Summary

This dataset is compiled for the binary classification of strokes from Head Computed Tomography (CT) scans. It is designed to train highly optimized Machine Learning and Deep Learning pipelines for rapid emergency triage and Clinical Decision Support Systems. Initially, the raw data contained three distinct classes: "No Stroke", "Bleeding", and "Ischemia". To optimize the dataset for an emergency detection system, the "Bleeding" and "Ischemia" classes were computationally merged into a unified "Stroke" class, resulting in a binary classification task (Stroke vs. No Stroke). To mitigate overfitting and ensure robust feature extraction, the original dataset was extensively augmented (applying random rotations up to ±10°, zoom shifts, and horizontal flips). The final dataset consists of 15,000 normalized tensor-ready images.

Repository Structure

The dataset is organized to support cross-validation training workflows and external generalization testing seamlessly:

  • dataset/: Contains all pre-processed, augmented, and validation CT scan images.
    • External_Dataset/: An independent dataset (sourced from Kaggle) used purely for external validation and testing model generalization across different scanner calibrations.
    • Fold1/: Training and validation split 1.
    • Fold2/: Training and validation split 2.
    • Fold3/: Training and validation split 3.

Inside each fold and the external dataset, the images are categorized into two sub-folders: Stroke and No-Stroke.

Source Data & Attribution

The data utilized to build this augmented dataset originates from two primary sources. In compliance with open data policies, please find the attributions below:

  1. Primary Dataset (Turkish Ministry of Health): The raw CT scans utilized to build the core augmented training folds were obtained from the Open Data Portal of the Republic of Turkey Ministry of Health.
  2. External Validation Dataset (Kaggle): An external dataset was used purely to test the robust generalization of the trained models across different scanner calibrations.

Licensing & Usage

This processed dataset is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

You are free to share and adapt this material for any purpose, even commercially, under the following terms:

  • Attribution: You must give appropriate credit to the original data sources (mentioned above) and indicate that this is an augmented, pre-processed version of the original files.

Disclaimer: This dataset is provided for research and educational purposes. It is not intended to replace professional medical diagnosis or serve as a standalone clinical tool.

Authors

  • Melis Kılıç
  • Esra Koç

Advisor: Assoc. Prof. Dr. Kali Gürkahran