CVPR 2026 Competition CT Scans For Lung Disease Diagnosis

Downstream datasets for the CVPR 2026 Foundation Models for General CT Image Diagnosis competition. The collection includes CT scans for lung cancer and COVID-19 detection, as referenced in published biomedical signal processing research. It was uploaded by author kmin06 in March 2026.

Use Cases

• Train 3D foundation models on CT scan volumes for general lung disease diagnosis
• Benchmark AI detection algorithms against radiologist performance for lung cancer
• Fine-tune segmentation networks using synthetic CT scan data
• Develop automated detection pipelines for COVID-19 from lung CT scan datasets

Strengths

• Dataset is associated with the CVPR 2026 conference competition, ensuring relevance to current computer vision research
• References peer-reviewed publications on automated deep learning networks for COVID-19 detection from CT scans
• Includes data for multiple lung pathologies, specifically lung cancer and COVID-19

Limitations

• Key quantitative details like row count, column features, and dataset size are unknown
• The specific composition and balance between lung cancer and COVID-19 cases are not detailed
• The extent and quality of synthetic data included are unspecified

Provenance

Source

Hugging Face, uploaded by user kmin06.

Collection Method

Curated as downstream datasets for a CVPR 2026 competition; references indicate inclusion of a large lung CT scan dataset from published research.

Time Range

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Freshness

Last updated March 2026.

Geography

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