Cardiac-CT: Cardiac CT Segmentation and Phenotyping Dataset

AI-CVM's Cardiac-CT dataset accompanies a research paper on a unified framework for cardiac CT segmentation and phenotyping. The dataset was used for human-in-the-loop annotation, vision foundation model development, and multicenter evaluation. It was last updated on July 15, 2026.

Use Cases

• Training segmentation models for cardiac structures based on the described human-in-the-loop annotations.
• Developing vision foundation models for medical imaging as referenced in the paper.
• Clinical validation of automated cardiac phenotyping algorithms using the multicenter evaluation data.

Strengths

• Dataset is associated with a formal research paper describing a unified framework for segmentation and phenotyping.
• Development involved a human-in-the-loop annotation process, suggesting iterative quality control.
• Evaluation included a multicenter study, which may indicate diverse data sources.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

AI-CVM, associated with the research paper authors.

Collection Method

Likely collected from clinical CT scans as part of a research framework involving human annotation.

Freshness

Last updated 2026-07-15 16:25:52; freshness should be verified.