A powerful new framework for understanding coral biomineralisation processes.

A newly published, open-access paper in Tomography of Materials and Structures presents a novel 4D in vivo µCT approach to track how corals build their skeletons in real time. By combining non-destructive X-ray imaging with advanced image analysis supported by Dragonfly 3D World, both skeletal growth and internal structural development were able to be quantified at micron-scale resolution across time. This results of this study provide a powerful new framework for understanding coral biomineralisation processes and lay the foundation for future studies investigating how coral growth responds to changing environmental conditions.

Study at a glance

Visualization performed in Dragonfly 3D World, of a S. pistillata fragment, showcasing timepoint to timepoint skeletal growth through the colored segmentations. 

Paper: In vivo X-ray computed microtomography: A novel approach to assess coral skeletal construction in the reef building coral Stylophora pistillata.

Imaging approach: In vivo micro computed tomography. In vivo uCT was used to repeatedly image the same S.Pistillata fragment on a weekly basis, resolving the development of the dynamic skeletal material.

Analysis approach: Automated image registration to align and correlate time-series datasets, followed by deep-learning segmentation to extract skeletal structures from relatively low signal-to-noise datasets.

What the researchers found

To assess the skeletal growth of the sample, the researchers took three scans over 16 days, and following registration and segmentation of the data, the authors were able to clearly demonstrate skeletal growth within the coral over time. Furthermore, the 4D composite datasets that were generated facilitated the quantification of skeletal volume, porosity, thickness, and timepoint-to-timepoint growth. 

  • Between timepoint 1 (Fig. 1Ai) and timepoint 2 (Figure 1Aii), skeletal volume increased from 629.09 mm3 to 661.57 mm3, or 4.64 mm3 per day, (+ 5.16% of skeletal volume overall)
  • Between timepoint 2 and timepoint 3 (Figure 1Aiii), skeletal volume increased to 702.75 mm3, or 5.88 mm3 per day from timepoint 2 (+ 6.22% of skeletal volume)
  • The average thickness of skeletal elements was 240 µm3 at timepoint 1, 244 µm3 at timepoint 2, and 246 µm3 at timepoint 3
  • Skeletal porosity remained relatively constant, decreasing slightly from 31.30% at timepoint 1, to 30.31% at timepoint 2, and 29.73% at timepoint 3

Figure 1: Serial scanning of S. pistillata permits the resolution of skeletal growth, between (Ai) timepoint 1 (TP1), (Aii) timepoint 2 (TP2) and (Aiii) timepoint 3 (TP3). Figures Bi-iii show this growth as a 3D render, (C) quantifying this growth. Voxel-by-voxel alignment between timepoints allows the generation of 4D µCT data, allowing the visualisation of micron-scale growth (D-E).  White asterisks highlight areas of skeletal thickening, while orange asterisks highlight vertical extension.

Significance of these findings

This novel approach to capturing the biomineralisation process represents a clear step change from traditional approaches such as linear extension measurements, buoyant weight, and photogrammetry. These conventional methods typically provide bulk or surface-derived estimates of growth and cannot resolve how skeletal material is deposited internally, nor how growth varies spatially across different regions of the skeleton. As a result, they obscure important heterogeneity and spatial intricacies of calcification processes.

In contrast, 4D in vivo µCT enables direct, non-destructive quantification of both external skeletal extension and internal thickening dynamics at micron-scale resolution through time. This allows growth to be resolved at the level of individual skeletal elements, permitting study of spatial variability in calcification rates such as elevated deposition at actively growing regions that would be masked in bulk measurements. Crucially, the ability to repeatedly image the same specimen provides a time-resolved, voxel-by-voxel record of skeletal development, offering a level of detail and reproducibility that is not achievable with existing techniques.

For reef science, this approach provides a powerful tool to link fine-scale growth dynamics with environmental conditions, improving our mechanistic understanding of how corals construct their skeletons and respond to stressors such as warming and ocean acidification. It also enables quantification of inter-individual variability and structural development, both of which are critical for predicting longer-term reef resilience. Beyond corals, this methodology is readily transferable to other marine calcifiers, including molluscs, echinoderms, and calcareous algae, opening new avenues to study biomineralisation across marine taxa. Ultimately, this represents a significant advance toward more process-based, predictive models of reef growth and degradation under future environmental change.

Where Dragonfly 3D World supported the workflow

Dragonfly 3D World performed a vital role in the image processing and analysis workflows used within the paper. The automated image registration tool was particularly useful for correlating time-series datasets, enabling precise voxel-by-voxel alignment across scans,  essential for resolving fine-scale skeletal growth and for avoiding a time consuming manual alignment process (this is especially crucial when scaling to larger experiments with multiple specimens and timepoints)

For image segmentation, Dragonfly 3D World’s deep learning tools were critical in extracting skeletal structures from relatively low signal-to-noise datasets, while the splitter function enabled the team to simultaneously display raw greyscale tomographic data alongside segmented volumes, greatly improving interpretability and communication of results.

Imaging brought particular challenges for the researchers as, compared to ex vivo scans of dried specimens, the signal-to-noise ratio was substantially lower due to rapid scan acquisition (~5 minutes), as well as imaging through seawater and containment vessels. Despite these limitations, Dragonfly 3D World’s deep learning segmentation tools allowed them to reliably resolve fine skeletal features. This was critical for extracting meaningful quantitative data from otherwise noisy datasets and ultimately made the in vivo imaging approach viable.

Read the paper

The full article is open access in Tomography of Materials and Structures: https://doi.org/10.1016/j.tmater.2026.100083

Acknowledgement

This work was led by a group of interdisciplinary scientists at the University of Southampton (J. Trend, T. Page, J. Kleboe, S.Mahajan, G.L. Foster) and the UoS Coral Reef Laboratory (C.D'Angelo, J.Weidenmann) which was essential for the culture and maintenance of the corals used in this research. This project was also undertaken with close collaborations with the Biomedical Imaging Unit, Muvis X-Ray Imaging Centre and the Biomedical Research Facility (K.Dexter, O.Katsamenis) hosted at Southampton General Hospital. 

Proudly supporting the academic community. 

If your work involves Dragonfly 3D World, and you'd like to see it published on our website, we would love to hear from you. Don’t hesitate to reach out via Dragonfly Social and submit your work via the Publication Submission space.  

Not yet a member?

Join Dragonfly Social

Sign Up