Colorectal cancer is one of the most common cancers in the world. By establishing a benchmark, SimCol3D aimed to facilitate data-driven navigation during colonoscopy. More details about the challenge and corresponding data can be found in the challenge paper on arXiv. 

The challenge consisted of simulated colonoscopy data and images from real patients. This data release encompasses the synthetic portion of the challenge. The synthetic data includes three different anatomies derived from real human CT scans. Each anatomy provides several randomly generated trajectories with RGB renderings, camera intrinsics, ground truth depths, and ground truth poses. In total, this dataset includes more than 37,000 labelled images. 

The real colonoscopy data used in the SimCol3D challenge consists of images extracted from the EndoMapper dataset. The real data is available on the EndoMapper Synapse page. 

The synthetic colonoscopy data is made available in this repository.