A Primary Chest X-ray Dataset of Normal and Pneumonia Cases from Epic Chittagong, Bangladesh
Description
๐ Steps to Reproduce This dataset contains a collection of primary chest X-ray images acquired from Epic Chittagong, Bangladesh. The dataset is designed for the study and development of deep learning and machine learning models for pneumonia detection and classification. This dataset contains 3,355 primary chest X-ray images collected from Epic Chittagong, Bangladesh, categorized into two classes: (1) Normal (2) Pneumonia ๐ Dataset Composition --------------------------------- Training Data : => Normal: 321 images => Pneumonia: 321 images => Total Training Samples: 642 Testing Data : ------------------- Normal: 1,363 images => Pneumonia: 1,350 images => Total Testing Samples: 2,713 ๐ Grand Total: 3,355 X-ray images ๐ Folder Structure : ------------------------- /Chest_Xray_EpicChittagong_Dataset/ โโโ train/ โ โโโ Normal/ โ โโโ Pneumonia/ โโโ test/ โ โโโ Normal/ โ โโโ Pneumonia/ ๐ท Image Details : ------------------------ Format: JPEG / PNG Modality: Chest X-ray (CXR) Color: Grayscale Source: Epic Chittagong, Bangladesh 2025 Status: Primary dataset (raw and unprocessed) ๐งช Applications : --------------------- => Pneumonia vs. Normal chest X-ray classification => Deep learning model training (CNN, transfer learning) => Benchmarking medical imaging algorithms => Computer-aided diagnosis (CAD) => Radiology research and teaching ๐ฌ Contact : ------------------ For questions or collaboration Md Irfanul Kabir Hira Email: erfanulkabirhira132@gmail.com ๐ Department of Computer Science and Engineering ๐๏ธ Institutions : -------------------- Epic Chittagong, Bangladesh National Institute of Textile Engineering and Research University of Dhaka ๐ Categories : ---------------------- Computer Science, Radiology, Health Sciences, Artificial Intelligence, Computer Vision, Medical Imaging, Pneumonia, Chest X-ray, Deep Learning, Machine Learning
Files
Steps to reproduce
๐ The folder structure is organized as follows: -------------------------------------------------------