Rectal Cancer CT Scan Images from 107 Patients for Segmentation Tasks

107 rectal cancer patient cases provide Computed Tomography (CT) imaging data for medical image analysis. The dataset originates from Problem B of the 2019 Teddy Cup Data Mining Challenge and has been filtered to exclude negative samples. Author Yuyan Bin uploaded this 48.8 MB ZIP file under a CC-BY-4.0 license.

Use Cases

• Train semantic segmentation models based on CT scan slices of rectal tumors.
• Benchmark medical image analysis algorithms based on a curated set of cancer patient scans.
• Develop computer-aided diagnosis tools based on annotated tumor regions implied by the segmentation task.

Strengths

• Contains CT imaging data from 107 distinct patient cases.
• Excludes negative samples, which may simplify model training for positive case identification.

Limitations

• Dataset size is relatively small at 48.8 MB, which may limit model complexity.
• Column-level documentation and sample data are unavailable, requiring manual inspection after download.
• The description lacks details on annotation quality, slice count per patient, and specific segmentation labels.

Provenance

Source

Problem B of the 2019 (7th) Teddy Cup Data Mining Challenge.

Collection Method

Computed Tomography (CT) imaging data collected from rectal cancer patients.

Freshness

Last updated 2026-05-12 08:53:55.