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. 2024 Jun 17;11(1):642.
doi: 10.1038/s41597-024-03476-w.

ForametCeTera, a novel CT scan dataset to expedite classification research of (non-)foraminifera

Joost Luijmes  1   2   3 , Tristan van Leeuwen  2   4 , Willem Renema  5   6
Affiliations

ForametCeTera, a novel CT scan dataset to expedite classification research of (non-)foraminifera

Joost Luijmes et al. Sci Data. .

Abstract

This paper introduces ForametCeTera, a pioneering dataset designed to address the challenges associated with automating the analysis of benthic foraminifera in sediment cores. Foraminifera are sensitive sentinels of environmental change and are a crucial component of carbonate-denominated ecosystems, such as coral reefs. Studying their prevalence and characteristics is imperative in understanding climate change. However, analysis of foraminifera contained in core samples currently requires washing, sieving and manual quantification. These methods are thus time-consuming and require trained experts. To overcome these limitations, we propose an alternative workflow utilizing 3D X-ray computational tomography (CT) for fully automated analysis, saving time and resources. Despite recent advancements in automation, a crucial lack of methods persists for segmenting and classifying individual foraminifera from 3D scans. In response, we present ForametCeTera, a diverse dataset featuring 436 3D CT scans of individual foraminifera and non-foraminiferan material following a high-throughput scanning workflow. ForametCeTera serves as a foundational resource for generating synthetic digital core samples, facilitating the development of segmentation and classification methods of entire core sample CT scans.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The conventional procedure of quantifying foraminifera. A core sample is subdivided, soaked in a (chemical) solution and rinsed, followed by (wet) sieving, separation, and classification and quantification of the species. The latter two steps are performed under a microscope.
Fig. 2
Fig. 2
The proposed procedure of quantifying foraminifera. A core sample is subdivided and CT scanned. An algorithm then quantifies the 3D CT reconstruction.
Fig. 3
Fig. 3
The specimen scanning procedure. From left to right, a sample of different specimens is split into groups by type and put in tubes with a filling medium, each tube is scanned following the same protocol, each group-scan is segmented producing density volumes of individual specimens.
Fig. 4
Fig. 4
Microscope images of the selected samples. (a) Alveolinella quoyi. (b) Operculina ammonoides. (c) Baculogypsinoides sphaerulata. (d) Marginopora santoensis. (e) γ, an example of non-foraminiferan material.
Fig. 5
Fig. 5
The dataset structure of ForametCeTera.
See this image and copyright information in PMC

References

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