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---
license: cc-by-nc-nd-4.0
tags:
- medical
- Chest X-Ray
- Medicine
- Computer Vision
- Segmentation
- Classification
- Machine Learning
task_categories:
- image-segmentation
- image-to-image
size_categories:
- n<1K
---
# Chest X-ray
The dataset consists of .dcm files containing **X-ray images of the thorax**. The images are **labeled** by the doctors and accompanied by corresponding annotations in JSON format. The annotations provide detailed information about the **organ structures** present in the chest X-ray images.
# The dataset is created on the basis of [Chest X-Ray Dataset](https://unidata.pro/datasets/chest-x-ray-image-dicom/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=chest-x-rays-dataset)
### Types of diseases and conditions in the dataset:
- **Petrifications**
- **Nodule/mass**
- **Infiltration/Consolidation**
- **Fibrosis**
- **Dissemination**
- **Pleural effusion**
- **Hilar enlargement**
- **Annular shadows**
- **Healed rib fracture**
- **Enlarged medinastium**
- **Rib fractures**
- **Pneumothorax**
- **Atelectasis**
## Statistics for the dataset:
The dataset aims to aid in the development and evaluation of algorithms for **automated detection and classification** of thoracic organ **abnormalities and diseases**.
The dataset is valuable for research in **neurology, radiology, and oncology**. It allows the development and evaluation of computer-based algorithms, machine learning models, and deep learning techniques for **automated detection, diagnosis, and classification** of these conditions.
# 💴 For Commercial Usage: Full version of the dataset includes 400+ chest x-rays of people with different conditions, leave a request on **[our website](https://unidata.pro/datasets/chest-x-ray-image-dicom/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=chest-x-rays-dataset)** to buy the dataset
# Content
### The dataset includes:
- **files**: includes x-ray scans in .dcm format,
- **annotations**: includes annotations in JSON format made for files in the previous folder,
- **visualizations**: includes visualizations of the annotations,
- **.csv file**: includes links to the fies and metadata
### File with the extension .csv includes the following information for each media file:
- **dcm_path**: link to access the .dcm file,
- **annotation_path**: link to access the file with annotation in JSON-format,
- **age**: age of the person in the x-ray scan,
- **sex**: gender of the person in the x-ray scan,
- **StudyInstanceUID**: id of the study,
- **Nodule/mass**: wheter nodule/mass is observed,
- **Dissemination**: wheter dissemination is observed,
- **Annular shadows**: wheter annular shadows are observed,
- **Petrifications**: wheter petrifications are observed,
- **Pleural effusion**: wheter pleural effusion is observed
# Medical data might be collected in accordance with your requirements.
**🚀 You can learn more about our high-quality unique datasets [here](https://unidata.pro/datasets/chest-x-ray-image-dicom/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=chest-x-rays-dataset)**
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