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--- |
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license: cc-by-nc-nd-4.0 |
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tags: |
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- medical |
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- Chest X-Ray |
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- Medicine |
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- Computer Vision |
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- Segmentation |
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- Classification |
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- Machine Learning |
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task_categories: |
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- image-segmentation |
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- image-to-image |
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size_categories: |
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- n<1K |
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--- |
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# Chest X-ray |
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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. |
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# 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) |
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### Types of diseases and conditions in the dataset: |
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- **Petrifications** |
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- **Nodule/mass** |
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- **Infiltration/Consolidation** |
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- **Fibrosis** |
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- **Dissemination** |
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- **Pleural effusion** |
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- **Hilar enlargement** |
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- **Annular shadows** |
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- **Healed rib fracture** |
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- **Enlarged medinastium** |
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- **Rib fractures** |
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- **Pneumothorax** |
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- **Atelectasis** |
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## Statistics for the dataset: |
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The dataset aims to aid in the development and evaluation of algorithms for **automated detection and classification** of thoracic organ **abnormalities and diseases**. |
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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. |
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# 💴 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 |
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# Content |
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### The dataset includes: |
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- **files**: includes x-ray scans in .dcm format, |
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- **annotations**: includes annotations in JSON format made for files in the previous folder, |
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- **visualizations**: includes visualizations of the annotations, |
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- **.csv file**: includes links to the fies and metadata |
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### File with the extension .csv includes the following information for each media file: |
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- **dcm_path**: link to access the .dcm file, |
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- **annotation_path**: link to access the file with annotation in JSON-format, |
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- **age**: age of the person in the x-ray scan, |
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- **sex**: gender of the person in the x-ray scan, |
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- **StudyInstanceUID**: id of the study, |
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- **Nodule/mass**: wheter nodule/mass is observed, |
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- **Dissemination**: wheter dissemination is observed, |
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- **Annular shadows**: wheter annular shadows are observed, |
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- **Petrifications**: wheter petrifications are observed, |
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- **Pleural effusion**: wheter pleural effusion is observed |
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# Medical data might be collected in accordance with your requirements. |
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**🚀 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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