Deep Learning Workflow and Dataset for Deep Learning Image Classification of Ulcerative Colitis and Colorectal Cancer

Inflammatory bowel disease (IBD) is a chronic inflammatory condition of the gastrointestinal tract characterized by the deregulation of immuno-oncology markers. IBD includes ulcerative colitis and Chron disease. Chronic active inflammation is a risk factor for the development of colorectal cancer (CRC). Deep learning is a form of machine learning that is applicable to computer vision, and it includes algorithms and workflows used for image processing, analysis, visualization, and algorithm development. This publication describes a dataset of histological images of ulcerative colitis, colorectal cancer (adenocarcinoma), and colon control. The samples were stained with hematoxylin and eosin, and immunohistochemically analyzed for LAIR1 and TOX2. The methods used for collecting and producing the data, analysis using convolutional neural networks (CNNs), where the dataset can be found, and information about its use are also described. This paper is the companion manuscript of the recently published article “Ulcerative Colitis, LAIR1 and TOX2 Expression, and Colorectal Cancer Deep Learning Image Classification Using Convolutional Neural Networks” published in Cancers 2024, 16, 4230. https://doi.org/10.3390/cancers16244230.