There are 5,863 X-Ray images (JPEG) and 2 categories (Pneumonia/Normal).
The original dataset is organized into 3 folders (train, test, val) and contains subfolders for each image category (Pneumonia/Normal). There are 5,863 X-Ray images (JPEG) and 2 categories (Pneumonia/Normal).
Our dataset in the platform collects the Normal images present in the original dataset in order to build a normative database of chest X-Ray images.
Chest X-ray images (anterior-posterior) were selected from retrospective cohorts of pediatric patients of one to five years old from Guangzhou Women and Children’s Medical Center, Guangzhou. All chest X-ray imaging was performed as part of patients’ routine clinical care.
For the analysis of chest x-ray images, all chest radiographs were initially screened for quality control by removing all low quality or unreadable scans. The diagnoses for the images were then graded by two expert physicians before being cleared for training the AI system. In order to account for any grading errors, the evaluation set was also checked by a third expert.
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Guangzhou Women and Children’s Medical Center, Guangzhou
Dataset size estimation
|Total size aprox.
|Session size aprox.
|Kaggle: Chest X-ray (normal)