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.
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Acknowledgments
We thank the reviewers for critically reading and clarifying important aspects of the manuscript. This work was supported by a University of Sheffield, Department of Infection, Immunity and Cardiovascular Disease, Imaging and Modelling Node Studentship. We are grateful to Aaron Savage and Rob Wilkinson for providing us with the tg(fli1a:Lifeact-mClover)\(^{sh{\textit{467}}}\) transgenic.
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Kugler, E., Chico, T., Armitage, P. (2018). Image Analysis in Light Sheet Fluorescence Microscopy Images of Transgenic Zebrafish Vascular Development. In: Nixon, M., Mahmoodi, S., Zwiggelaar, R. (eds) Medical Image Understanding and Analysis. MIUA 2018. Communications in Computer and Information Science, vol 894. Springer, Cham. https://doi.org/10.1007/978-3-319-95921-4_32
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