Abstract
The zebrafish is an established vertebrate model to study development and disease of the cardiovascular system. Using transgenic lines and state-of-the-art microscopy it is possible to visualize the vascular architecture non-invasively, in vivo over several days. Quantification of the 3D vascular architecture would be beneficial to objectively and reliably characterise the vascular anatomy. So far, no method is available to automatically quantify the 3D cardiovascular system of transgenic zebrafish, which would enhance their utility as a pre-clinical model. Vascular segmentation is essential for any subsequent quantification, but due to the lack of a segmentation “gold standard” for the zebrafish vasculature, no in-depth assessment of vascular segmentation methods in zebrafish has been performed. In this study, we examine vascular enhancement using the Sato et al. enhancement filter in the Fiji image analysis framework and optimise the filter scale parameter for typical vessels of interest in the zebrafish cranial vasculature; and present methodological approaches to address the lack of a segmentation gold-standard of the zebrafish vasculature.
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Acknowledgments
This work was supported by a University of Sheffield, Department of Infection, Immunity and Cardiovascular Disease, Imaging and Modelling Node Studentship awarded to EK. The Zeiss Z1 light-sheet microscope was funded via British Heart Foundation Infrastructure Award awarded to TC.
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Kugler, E., Chico, T., Armitage, P.A. (2020). Validating Segmentation of the Zebrafish Vasculature. In: Zheng, Y., Williams, B., Chen, K. (eds) Medical Image Understanding and Analysis. MIUA 2019. Communications in Computer and Information Science, vol 1065. Springer, Cham. https://doi.org/10.1007/978-3-030-39343-4_23
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DOI: https://doi.org/10.1007/978-3-030-39343-4_23
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