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Tuberculosis (TB) Chest X-ray Dataset for Automated Classification (4,200 Images)

Domaine:

healthcare

Type de record:

dataset
Créateur:
Kad
Éditeur:
Zenodo
Hôte:avatar
This dataset contains a curated collection of 4,200 frontal chest X-ray (CXR) images designed for the automated detection and binary classification of pulmonary Tuberculosis (TB). The data is categorized into two classes: TB-positive (700 samples) and Normal (healthy) cases (3500 samples). This specific 4,200-image collection was utilized for the training, validation, and testing of computationally efficient hybrid deep learning architectures (specifically Vision Transformers) aimed at resource-constrained clinical environments. Origin & Attribution: This data is a specific subset/split derived from the larger public Tuberculosis (TB) Chest X-ray Database (initially curated by researchers from Qatar University and the University of Dhaka on Kaggle). The underlying images aggregate radiological scans from well-known public health sources, including: The National Library of Medicine (NLM) Montgomery and Shenzhen datasets The National Institute of Allergy and Infectious Diseases (NIAID) TB Portal The RSNA Pneumonia Detection Challenge dataset Structure & Format: To bypass file limits and preserve the internal folder structure, the 4,200 images have been compressed into a single .zip archive. The images are suitable for immediate preprocessing and integration into standard computer vision and deep learning pipelines.

Visit

doi.orgzenodo.org

Tasks

computer visionimage classification

Licenses

Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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