Motivation

There have been great advancements in the field of digital pathology. The surge in development of analytical methods for such data makes it crucial to develop benchmark synthetic datasets for objectively validating and comparing these methods. In addition, developing a detailed model of the tumour microenvironment can aid our understanding of the underpinning laws of tumour heterogeneity.

Results

We propose a model of the healthy and cancerous colonic crypt microenvironment. Our model is designed to generate synthetic histology image data with parameters that allow control over cancer grade, cellularity, cell overlap ratio, image resolution, and objective level. To the best of our knowledge, ours is the first model to simulate histology image data at subcellular level for healthy and cancerous colon tissue, where the cells have several compartments and are organized to mimic the microenvironment of tissue in situ rather than dispersed cells in a cultured environment. The simulated data could be used to validate techniques such as image restoration, cell and crypt segmentation, and cancer grading.

Download

Download software and example data for healthy, well differentiated, moderately differentiated and poorly differentiated images. All code is generated using MATLAB. The data files show .png images for the H&E images generated, the cell boundaries and crypt segmentation. They also contain the data in a mat file. Please note that the data files are of size around 500MG.