Kugler, E. orcid.org/0000-0003-2536-6140, Plant, K., Chico, T. orcid.org/0000-0002-7458-5481 et al. (1 more author) (2019) Enhancement and Segmentation Workflow for the Developing Zebrafish Vasculature †. Journal of Imaging, 5 (1). 14. ISSN 2313-433X
Abstract
Zebrafish have become an established in vivo vertebrate model to study cardiovascular development and disease. However, most published studies of the zebrafish vascular architecture rely on subjective visual assessment, rather than objective quantification. In this paper, we used state-of-the-art light sheet fluorescence microscopy to visualize the vasculature in transgenic fluorescent reporter zebrafish. Analysis of image quality, vascular enhancement methods, and segmentation approaches were performed in the framework of the open-source software Fiji to allow dissemination and reproducibility. Here, we build on a previously developed image processing pipeline; evaluate its applicability to a wider range of data; apply and evaluate an alternative vascular enhancement method; and, finally, suggest a work-flow for successful segmentation of the embryonic zebrafish vasculature.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019. The authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | 3D; analysis; development; in vivo; light sheet fluorescence microscopy (LSFM); segmentation; vasculature; zebrafish |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Sheffield Teaching Hospitals |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Mar 2019 10:31 |
Last Modified: | 07 Mar 2019 10:31 |
Published Version: | https://doi.org/10.3390/jimaging5010014 |
Status: | Published |
Publisher: | MDPI |
Refereed: | Yes |
Identification Number: | 10.3390/jimaging5010014 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:142358 |