Towards understanding speciation by automated extraction and description of 3D foraminifera stacks
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...
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ftcardiffmetufig:oai:figshare.com:article/19433963 2023-05-15T18:00:36+02:00 Towards understanding speciation by automated extraction and description of 3D foraminifera stacks Wenshu Zhang Thomas Ezard Alex Searle-Barnes Anieke Brombacher Orestis Katsamenis Mark Nixon 2020-05-18T00:00:00Z https://figshare.com/articles/conference_contribution/Towards_understanding_speciation_by_automated_extraction_and_description_of_3D_foraminifera_stacks/19433963 unknown 10779/cardiffmet.19433963.v1 https://figshare.com/articles/conference_contribution/Towards_understanding_speciation_by_automated_extraction_and_description_of_3D_foraminifera_stacks/19433963 In Copyright Bioinformatics and computational biology not elsewhere classified Three dimension 3D image segmentation Biology image reconstruction manuals computer vision Text Conference contribution 2020 ftcardiffmetufig 2022-04-06T23:05:40Z 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. Conference Object Planktonic foraminifera Cardiff Metropolitan University: Figshare |
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Cardiff Metropolitan University: Figshare |
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Bioinformatics and computational biology not elsewhere classified Three dimension 3D image segmentation Biology image reconstruction manuals computer vision |
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Bioinformatics and computational biology not elsewhere classified Three dimension 3D image segmentation Biology image reconstruction manuals computer vision Wenshu Zhang Thomas Ezard Alex Searle-Barnes Anieke Brombacher Orestis Katsamenis Mark Nixon Towards understanding speciation by automated extraction and description of 3D foraminifera stacks |
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Bioinformatics and computational biology not elsewhere classified Three dimension 3D image segmentation Biology image reconstruction manuals computer vision |
description |
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. |
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Conference Object |
author |
Wenshu Zhang Thomas Ezard Alex Searle-Barnes Anieke Brombacher Orestis Katsamenis Mark Nixon |
author_facet |
Wenshu Zhang Thomas Ezard Alex Searle-Barnes Anieke Brombacher Orestis Katsamenis Mark Nixon |
author_sort |
Wenshu Zhang |
title |
Towards understanding speciation by automated extraction and description of 3D foraminifera stacks |
title_short |
Towards understanding speciation by automated extraction and description of 3D foraminifera stacks |
title_full |
Towards understanding speciation by automated extraction and description of 3D foraminifera stacks |
title_fullStr |
Towards understanding speciation by automated extraction and description of 3D foraminifera stacks |
title_full_unstemmed |
Towards understanding speciation by automated extraction and description of 3D foraminifera stacks |
title_sort |
towards understanding speciation by automated extraction and description of 3d foraminifera stacks |
publishDate |
2020 |
url |
https://figshare.com/articles/conference_contribution/Towards_understanding_speciation_by_automated_extraction_and_description_of_3D_foraminifera_stacks/19433963 |
genre |
Planktonic foraminifera |
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Planktonic foraminifera |
op_relation |
10779/cardiffmet.19433963.v1 https://figshare.com/articles/conference_contribution/Towards_understanding_speciation_by_automated_extraction_and_description_of_3D_foraminifera_stacks/19433963 |
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In Copyright |
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1766169765459525632 |