image
imagewidth (px) 1.37k
3.48k
| type
stringclasses 17
values |
---|---|
abscess |
|
abscess |
|
abscess |
|
abscess |
|
abscess |
|
abscess |
|
abscess |
|
abscess |
|
abscess |
|
ards |
|
ards |
|
atelectasis |
|
atelectasis |
|
atelectasis |
|
atelectasis |
|
atelectasis |
|
atelectasis |
|
atelectasis |
|
atherosclerosis_of_the_aorta |
|
atherosclerosis_of_the_aorta |
|
atherosclerosis_of_the_aorta |
|
atherosclerosis_of_the_aorta |
|
atherosclerosis_of_the_aorta |
|
atherosclerosis_of_the_aorta |
|
cardiomegaly |
|
cardiomegaly |
|
cardiomegaly |
|
cardiomegaly |
|
cardiomegaly |
|
cardiomegaly |
|
cardiomegaly |
|
cardiomegaly |
|
emphysema |
|
emphysema |
|
emphysema |
|
emphysema |
|
emphysema |
|
fracture |
|
fracture |
|
fracture |
|
fracture |
|
fracture |
|
fracture |
|
hydropneumothorax |
|
hydropneumothorax |
|
hydropneumothorax |
|
hydropneumothorax |
|
hydropneumothorax |
|
hydropneumothorax |
|
hydropneumothorax |
|
hydropneumothorax |
|
hydropneumothorax |
|
hydrothorax |
|
hydrothorax |
|
hydrothorax |
|
hydrothorax |
|
hydrothorax |
|
pneumonia |
|
pneumonia |
|
pneumonia |
|
pneumonia |
|
pneumonia |
|
pneumosclerosis |
|
pneumosclerosis |
|
pneumosclerosis |
|
pneumosclerosis |
|
post_inflammatory_changes |
|
post_inflammatory_changes |
|
post_inflammatory_changes |
|
post_inflammatory_changes |
|
post_inflammatory_changes |
|
post_inflammatory_changes |
|
post_inflammatory_changes |
|
post_traumatic_ribs_deformation |
|
post_traumatic_ribs_deformation |
|
post_traumatic_ribs_deformation |
|
post_traumatic_ribs_deformation |
|
post_traumatic_ribs_deformation |
|
sarcoidosis |
|
sarcoidosis |
|
sarcoidosis |
|
sarcoidosis |
|
sarcoidosis |
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sarcoidosis |
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scoliosis |
|
scoliosis |
|
scoliosis |
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scoliosis |
|
tuberculosis |
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tuberculosis |
|
tuberculosis |
|
tuberculosis |
|
tuberculosis |
|
venous_congestion |
|
venous_congestion |
|
venous_congestion |
|
venous_congestion |
Chest X-ray - Object Detection dataset
The dataset consists of a collection of chest X-ray images in .jpg and .dcm formats. The images are organized into folders based on different medical conditions related to the chest. Each folder contains images depicting specific chest abnormalities.
💴 For Commercial Usage: Full version of the dataset includes much more chest x-rays of people with different conditions, leave a request on TrainingData to buy the dataset
Types of diseases and conditions in the dataset:
Abscess, Ards, Atelectasis, Atherosclerosis of the aorta, Cardiomegaly, Emphysema, Fracture, Hydropneumothorax, Hydrothorax, Pneumonia, Pneumosclerosis, Post inflammatory changes, Post traumatic ribs deformation, Sarcoidosis, Scoliosis, Tuberculosis and Venous congestion
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.
💴 Buy the Dataset: This is just an example of the data. Leave a request on https://trainingdata.pro/datasets to discuss your requirements, learn about the price and buy the dataset
Content
The folder "files" includes 17 folders:
- corresponding to name of the disease/condition and including x-rays of people with this disease/condition (abscess, ards, atelectasis etc.)
- including x-rays in 2 different formats: .jpg and .dcm.
File with the extension .csv includes the following information for each media file:
- dcm: link to access the .dcm file,
- jpg: link to access the .jpg file,
- type: name of the disease or condition on the x-ray
Medical data might be collected in accordance with your requirements.
TrainingData
More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets
TrainingData's GitHub: https://github.com/trainingdata-pro
keywords: lungs, heart, blood vessels, airways, ribs, lymph nodes, upper abdomen, cough, breath, structures, radiograph, scan, chest pain, fever, chest symptoms, chest dataset, chest X-rays dataset, scoliosis detection dataset, scoliosis segmentation dataset, scoliosis image dataset, medical imaging, radiology dataset, spine deformity dataset, orthopedic abnormalities, scoliotic curve dataset, degenerative spinal conditions, diagnostic imaging, medical imaging, radiology dataset, image dataset, abnormalities detection, chest anatomy, health, formations, imaging procedure, x-rays measurements, machine learning, computer vision, deep learning
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