Clinically validated dataset of 435 human colons segmented from CT colonography.
Authors
Affiliations (6)
Affiliations (6)
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark. [email protected].
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.
- Department of Radiology, Bispebjerg Hospital, Copenhagen, Denmark.
- Copenhagen Academy for Medical Education and Simulation, Center for Human Resources and Education, The Capital Region of Denmark, Copenhagen, Denmark.
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.
- Neurobiology Research Unit, Copenhagen University Hospital, Copenhagen, Denmark.
Abstract
High-quality segmentation datasets are essential for advancing AI applications in medical imaging. However, it is challenging to generate such datasets for highly variable and complex organs like the colon. We introduce a dataset of 435 human colons, segmented from Computed Tomography Colonography (CTC) obtained from the publicly available The Cancer Imaging Archive (TCIA). Each scan includes a mask of the whole colon, including collapsed segments and the fluid, and a mask of only the gas-filled parts of the colon. The colon segmentation accuracy has been clinically validated by an expert abdominal radiologist. This is the first open-access dataset of segmented colons derived from CTC. This resource enables population-scale radiologic studies, supports the development of AI-based image analysis tools, and facilitates the creation of anatomically accurate digital models and simulators, both virtual and physical.