Kugler, E., Chico, T. orcid.org/0000-0002-7458-5481 and Armitage, P. (2018) Image analysis in light sheet fluorescence microscopy images of transgenic zebrafish vascular development. In: Nixon, M., Mahmoodi, S. and Zwiggelaar, R., (eds.) Medical Image Understanding and Analysis. MIUA 2018, 09-11 Jul 2018, Southampton, UK. Communications in Computer and Information Science, 894 . Springer Nature Switzerland AG , pp. 343-353. ISBN 9783319959207
Abstract
The zebrafish has become an established model to study vascular development and disease in vivo. However, despite it now being possible to acquire high-resolution data with state-of-the-art fluorescence microscopy, such as lightsheet microscopy, most data interpretation in pre-clinical neurovascular research relies on visual subjective judgement, rather than objective quantification. Therefore, we describe the development of an image analysis workflow towards the quantification and description of zebrafish neurovascular development. In this paper we focus on data acquisition by lightsheet fluorescence microscopy, data properties, image pre-processing, and vasculature segmentation, and propose future work to derive quantifications of zebrafish neurovasculature development.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2018 Springer Nature Switzerland AG. This is an author produced version of a paper subsequently published in Medical Image Understanding and Analysis. Uploaded in accordance with the publisher's self-archiving policy. |
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: | 21 Sep 2018 10:30 |
Last Modified: | 22 Sep 2018 03:16 |
Published Version: | https://doi.org/10.1007/978-3-319-95921-4_32 |
Status: | Published |
Publisher: | Springer Nature Switzerland AG |
Series Name: | Communications in Computer and Information Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-319-95921-4_32 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:135960 |