1aurent/Kather-texture-2016
The dataset represents a texture collection of human colorectal cancer histology images. It contains 5,000 RGB images of size 150 × 150 px (74 µm × 74 µm), each belonging to one of eight tissue classes. Images were digitized at 20× magnification (0.495 µm/pixel) using an Aperio ScanScope (Leica Biosystems). The samples are formalin‑fixed, paraffin‑embedded (FFPE) colorectal adenocarcinoma tissues from pathology archives, fully anonymized and approved by an ethics committee.
Dataset description and usage context
Colorectal Cancer Histology Texture Dataset
Description
- License: CC‑BY‑4.0
- Size Category: 1K < n < 10K
- Task Category: Image Classification
- Tags:
- Biology
- Colorectal Cancer
- Histopathology
- Histology
- Digital Pathology
Configuration
- Default Split:
- Split: train
- Path: data/train-*
Information
-
Features:
- Image: type image
- Label: categorical with classes:
- 0 ADIPOSE
- 1 COMPLEX
- 2 DEBRIS
- 3 EMPTY
- 4 LYMPHO
- 5 MUCOSA
- 6 STROMA
- 7 TUMOR
-
Split: train – 5,000 samples, 329 215 083 bytes
-
Download Size: 293 441 024 bytes
-
Dataset Size: 329 215 083 bytes
Pair the dataset with AI analysis and content workflows.
Once the source passes your review, move straight into summarization, transformation, report drafting, or presentation generation with the JuheAI toolchain.