Bioimaging Challenge 2015 Breast Histology Dataset

This dataset contains breast histology images from four classes: normal, benign, in situ carconima and invasive carcinoma. A trained Convolutional Neural Network for the classification of these images is also available. To access the dataset please request your password via the link http://bioimglab.inesctec.pt/?page_id=893 and fill the form.

Users of this dataset should cite the following article: Teresa Araújo, Guilherme Aresta, Eduardo Castro, José Rouco, Paulo Aguiar, Catarina Eloy, António Polónia, and Aurélio Campilho, Classification of Breast Cancer Histology Images Using Convolutional Neural Networks, PLOS ONE, 2017. Available at: https://doi.org/10.1371/journal.pone.0177544

Please also refer the link of the dataset download page (this page): https://rdm.inesctec.pt/dataset/nis-2017-003

In addition, we appreciate to hear about any publications that use this dataset. The contact e-mail is tfaraujo@inesctec.pt.

Data and Resources

Additional Info

Field Value
Author Teresa Araújo, Guilherme Aresta, Eduardo Castro, José Rouco, Paulo Aguiar, Catarina Eloy, António Polónia, Aurélio Campilho
Last Updated September 19, 2017, 13:49 (Europe/Lisbon)
Created April 21, 2017, 13:17 (Europe/Lisbon)
dc.Coverage.Spatial Images acquired from patients in Porto and Covilhã
dc.Coverage.Temporal Between october 2014 and march 2015
dc.Date April and October 2015
dc.Format *.tiff, *.py
dc.Format.Extent 2,53GB
dc.Publisher FEUP, INESC TEC, i3S, INEB, Ipatimup, FMUP
dc.Relation Teresa Araújo, Guilherme Aresta, Eduardo Castro, José Rouco, Paulo Aguiar, Catarina Eloy, António Polónia, and Aurélio Campilho, Classification of Breast Cancer Histology Images Using Convolutional Neural Networks, PLOS ONE, 2017. Available at: https://doi.org/10.1371/journal.pone.0177544
dc.Type breast cancer histology images; convolutional neural network pyhton code