Commercial
CT Scan Chest Dataset
It is a large-scale CT scan chest dataset featuring over 150,000 chest CT images with annotated pathologies, designed for training deep learning models in lung disease detection, cancer diagnosis, and medical imaging tasks, with labeled data covering a wide range of conditions such as pulmonary embolism, tuberculosis, and lung cancer.
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-
- studies with protocol
- 50,000+
-
- studies without protocol
- 100,000+
-
- pathologies
- 24
- Medicine
- Computer vision
- Machine Learning
- Segmentation
- Classification
-
- studies with protocol
- 50,000+
-
- studies without protocol
- 100,000+
-
- pathologies
- 24
Dataset Info
Characteristic | Data |
Description | Chest CT scans with or without protocols |
Data types | DiCOM |
Markup | Segmentation of pathologies |
Tasks | Pathology recognition, computer vision. |
Number of studies | 150,000+ |
Labeling | Information about each study, including target pathology (1 for presence, 0 for absence) |
Pathologies | Developmental anomalies of the lower airways, Destruction/abscess of the lung, Chest soft tissue changes (breast or mammary gland masses), Pulmonary embolism, Pulmonary airflow disorders, Lung cancer, Osteoporosis, Osteoporosis, Hydrothorax, Coronary calcium, Aortic aneurysm, Pulmonary trunk diameter, Lymph nodes, Pulmonary emphysema, Tuberculosis, Sarcoidosis. |
Technical
Characteristics
Characteristic | Data |
File extension | DiCOM |
Extension of labeling file | csv |
Dataset Use Cases
FAQs
What are the technical characteristics of CT Scan Chest Dataset?
The dataset is stored in DiCOM files with annotations in CSV format. It includes detailed information for each study, covering 3D chest imaging, radiology reports, and pathology segmentation for advanced machine learning research.
Does the dataset include radiology reports or text metadata?
Yes, each study includes structured radiology text and metadata annotations. These details provide insights into chest computed tomography scans, patient demographics, and radiology findings, which are crucial for diagnostic imaging models.
Which medical conditions are covered in this CT Scan Chest Dataset?
The dataset covers a broad spectrum of lung diseases and related conditions, including pulmonary airflow disorders, osteoporosis, hydrothorax, aortic aneurysm, sarcoidosis, and pulmonary embolism. This variety makes it useful for training data in multiple medical imaging applications.
Can I request a sample of the dataset before purchase?
Yes, Unidata provides samples upon request. This allows you to verify CT images, DiCOM format compatibility, and annotation quality before using them in deep learning or machine learning workflows.
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