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.
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Data availability
The dataset is hosted in the Open Science Framework (OSF) repository “HQColon: High-Resolution Human Colon Segmentation” (https://doi.org/10.17605/OSF.IO/8TKPM).
Code availability
The code for the semi-automatic segmentation of the colon can be found in the following GitHub repository https://github.com/horizon-europe-2023-ire/colon-segmentation-dataset. The RootPainter project for segmenting the colon fluid is available in the folder “root_painter_colon_fluid_project.zip” of the OSF repository11.
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Acknowledgements
This work is funded by the European Union, grant number 101135082. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. Abraham George Smith is funded by Novo Nordisk Foundation Grant [NNF22OC0080177].
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Martina Finocchiaro designed and implemented the segmentation methods with contributions from Ronja Stern and Abraham George Smith; performed post-processing, quality checks and manual corrections of the segmentatios; designed the clinical validation protocol with input from Kristoffer Cold and Lars Konge; designed and developed the interface for clinical validation; analyzed the results and wrote the manuscript. Martina Finocchiaro and Ronja Stern created the data and code repositories. Rikke Vilhelmsborg clinically validated the segmentations. Kenny Erleben advised on the technical content of the research project. Melanie Ganz supervised and coordinated the research project. All authors reviewed and edited the manuscript.
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Finocchiaro, M., Stern, R., Vilhelmsborg, R. et al. Clinically validated dataset of 435 human colons segmented from CT colonography. Sci Data (2026). https://doi.org/10.1038/s41597-025-06518-z
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DOI: https://doi.org/10.1038/s41597-025-06518-z
