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Surfice: visualizing neuroimaging meshes, tractography streamlines and connectomes

Nature Methods volume 22, pages 1615–1616 (2025)Cite this article

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Visualization of surface meshes, tractography fibers and connectomes aids neuroimaging inference and communication. Surfice reads and displays various popular neuroimaging formats, using specialized shader programs that can display surface and embedded structures simultaneously. Python scripting enhances usability for both new and advanced users, enabling task automation. By dividing tasks between the complementary voxel-based MRIcroGL and vertex-based Surfice interfaces, users can efficiently manage complex data without an overwhelming user interface.

While medical imaging data are acquired volumetrically, it is often useful to represent the data in other geometries, such as cortical surface meshes1. Additionally, diffusion-weighted data can be used to estimate fiber tracts, which are often modeled and visualized as streamlines1,2.

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Fig. 1: Surfice user interface and visualization capabilities for cortical and subcortical structures.

Code availability

Surfice is free open-source software available under the permissive BSD 2-Clause license. Source code is available via GitHub at https://github.com/neurolabusc/surf-ice. Compiled code and MediaWiki are available at https://www.nitrc.org/projects/surfice/.

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Acknowledgements

C.R. was supported by NIH RF1-MH133701 and P50-DC01466.

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  1. McCausland Center for Brain Imaging, Department of Psychology, University of South Carolina, Columbia, SC, USA

    Christopher Rorden

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  1. Christopher Rorden
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Correspondence to Christopher Rorden.

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The author declares no competing interests.

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Nature Methods thanks Michel Thiebaut de Schotten, J. Donald Tournier and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Rorden, C. Surfice: visualizing neuroimaging meshes, tractography streamlines and connectomes. Nat Methods 22, 1615–1616 (2025). https://doi.org/10.1038/s41592-025-02764-6

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