Towards understanding speciation by automated extraction and description of 3D foraminifera stacks.pdf (5.29 MB)
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Towards understanding speciation by automated extraction and description of 3D foraminifera stacks

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conference contribution
posted on 31.03.2022, 10:42 by Wenshu Zhang, Thomas Ezard, Alex Searle-Barnes, Anieke Brombacher, Orestis Katsamenis, Mark Nixon

The sheer volume of 3D data restricts understanding of genetic speciation when analyzing specimens of planktonic foraminifera and so we develop an end-to-end computer vision system to solve and extend this. The observed fossils are planktonic foraminifera, which are single-celled organisms that live in vast numbers in the world’s oceans. Each foram retains a complete record of its size and shape at each stage along its journey through life. In this study, a variety of individual foraminifera are analyzed to study the differences among them and compared with manually labelled ground truth. This is an approach which (i) automatically reconstructs individual chambers for each specimen from image sequences, (ii) uses a shape signature to describe different types of species. The automated analysis by computer vision gives insight that was hitherto unavailable in biological analysis: analyzing shape implies understanding spatial arrangement and this is new to the biological analysis of these specimens. By processing datasets of 3D samples containing 9GB of points, we show that speciation can indeed now be analyzed and that automated analysis from morphological features leads to new insight into the origins of life.


Funding

This work was funded by the Natural Environment Research Council award NE/P019269/1. The authors thank μ-VIS X-ray Imaging Centre at University of Southampton for supporting micro-CT scanning of foreminifera.

History

Presented at

Conference paper presented at 2020 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), 29-31 March 2020

Published in

2020 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI)

Publisher

IEEE

Version

AM (Accepted Manuscript)

Citation

Zhang, W., Ezard, T., Searle-Barnes, A., Brombacher, A., Katsamenis, O. and Nixon, M. (2020) 'Towards Understanding Speciation By Automated Extraction And Description Of 3d Foraminifera Stacks', 2020 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) (pp. 30-33). IEEE.

Electronic ISSN

2473-3598

ISBN

978-1-7281-5745-0

Cardiff Met Affiliation

  • Cardiff School of Technologies

Cardiff Met Authors

Wenshu Zhang

Copyright Holder

© The Publisher

Publisher Rights Statement

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Language

en