Colorectal cancer histological dataset

Please cite the following paper if you use this dataset

Ponzio, F.; Macii, E.; Ficarra, E.; Di Cataldo, S. Colorectal Cancer Classification using Deep Convolutional Networks - An Experimental Study. In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies–Volume 2: BIOIMAGING, INSTICC, SciTePress, Madeira, Portugal, 19–21 January 2018; pp. 58–66.

Samples

Samples were

• obtained from http://www.virtualpathology.leeds.ac.uk/.
• stained with hematoxylin and eosin (HE).
• from colon tissue.

Diagnosis was confirmed by a pathologist.

Train and test folders

Patients among train and test are different.

• 9000 images (18 patients, 6 per class) for train (see train folder).
• 4500 images (9 patients, 3 per class) for test (see test folder).

Classes

• AC: Adenocarcinoma
• AD: Tubulovillous adenoma
• H: Healthy tissue