Colorectal Cancer Histology Image Tiles for Tissue Multi-class Classification

<p><strong>Content</strong></p> <p>The present dataset is linked to a research aimed at discovering the best normalization pipeline and classification model for colorectal cancer multi-class tissue classification.<br> The 15,856 histological image tiles are completely anomized and are extracted from 10 formalin-fized paraffine-embedded samples of patients affected by colorectal cancer.</p> <p>The materials are inside the following zip file:</p> <p>&ldquo;CRC_Tiles_IRCCS_ISTITUTO_TUMORI_BARI.zip&rdquo;: a zipped folder containing tiles (n=15,856) annotated by a pathologist, grouped in 6 subdirectories, each of them representing a class. Tiles are of size 224 x 224 px, taken at a resolution of 0.5 &mu;m/px.<br> <br> <strong>Ethical Statement</strong></p> <p>The study has been funded by &ldquo;Tecnopolo per la Medicina di Precisione (CUP B84I18000540002)&rdquo;. The institutional Ethic Committee approved the study (Prot n. 780/CE).</p> <p><br> <strong>Related Datasets and Works</strong><br> &nbsp;<br> For further details concerning the aforementioned dataset, refer to the papers below.&nbsp;<br> Please cite the following&nbsp;articles if you need this dataset for your research.</p> <p>Altini N. et al. (2021) Multi-class Tissue Classification in Colorectal Cancer with Handcrafted and Deep Features. In: Huang DS., Jo KH., Li J., Gribova V., Bevilacqua V. (eds) Intelligent Computing Theories and Application. ICIC 2021. Lecture Notes in Computer Science, vol 12836. Springer, Cham.&nbsp;<br> https://doi.org/10.1007/978-3-030-84522-3_42</p> <p>Altini, N., Marvulli, T. M., Zito, F. A., Caputo, M., Tommasi, S., Azzariti, A., ... &amp; Bevilacqua, V. (2023). The Role of Unpaired Image-to-Image Translation for Stain Color Normalization in Colorectal Cancer Histology Classification.&nbsp;<em>Computer Methods and Programs in Biomedicine</em>, 107511.&nbsp;<br> <a href="https://doi.org/10.1016/j.cmpb.2023.107511">https://doi.org/10.1016/j.cmpb.2023.107511</a></p> <p>Please also consider the dataset offered in our previous work:</p> <p>Altini N. et al. (2021). Pathologist&#39;s Annotated Image Tiles for Multi-Class Tissue Classification in Colorectal Cancer (v1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.4785131</p>