Commercial
Chest CT Segmentation Dataset
T scans includes over 1,000 studies that highlight various pathologies such as cancer, emphysema, hydrothorax, and etc
Request a demo- Medicine The use of machine learning in the medicine
- Segmentation Dividing an image into semantically independent segments to determine object boundaries
- Computer Vision The ability to recognize and analyze images and videos
- Classification Process of recognition and grouping of objects into preset categories
- Oncology Focused on the identification and analysis of cancerous lesions in imaging studies
- 1,000+
- studies
- 7
- pathologies
- 8
- anatomical region
CASE DESCRIPTION
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The dataset contains 1000 studies. The data format is nii.
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It includes detailed segmentation masks for 8 anatomical regions
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The dataset includes both volumetric data and corresponding masks for each study.
Application areas of the dataset
-
01.
Medical diagnostics:
Computer vision and classification for automatic detection and classification of various chest pathologies -
02.
Clinical Decision Support Systems:
The dataset can enhance decision-making tools by providing accurate segmentation data that assist healthcare professionals in interpreting CT scans. -
03.
Training Medical Personnel:
Segmentation for the education and training of medical university students, interns, and residents -
04.
Anatomical Segmentation:
Develop algorithms for automatic delineation of anatomical structures.
Pathologies
- cancer
- aeration disorder
- hydrothorax
- emphysema
- paracardiac fat
- coronary calcium
Anatomical regions
- ribs
- lungs
- aorta
- pulmonary trunk
- heart
- sternum
- costal cartilages
- spine
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