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Brain micro-vasculature imaging: An unsupervised deep learning algorithm for segmenting mouse brain volume probed by high-resolution phase-contrast X-ray tomography

Academic Article
Publication Date:
2020
abstract:
High-throughput synchrotron-based tomographic microscopy at third genera- tion light sources allows to probe cm-sized samples at micrometer-resolution. In this work, we present an approach to image a full mouse brain. With Indian- ink as a contrast agent, it was possible to obtain 3D distribution of microvessels while a computational framework automatically extracted the morphological and geometrical embedding of the putative vascular systems. Results demon- strate the potentiality of the proposed methodology to visualize and quantify in 3D details of the brain tissue with an image quality and resolution previously unachievable.
Iris type:
01.01 Articolo in rivista
Keywords:
brain circulation; microvasculature; image segmentation; x-ray synchrotron
List of contributors:
Zippo, ANTONIO GIULIANO
Authors of the University:
ZIPPO ANTONIO GIULIANO
Handle:
https://iris.cnr.it/handle/20.500.14243/379574
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URL

https://onlinelibrary.wiley.com/doi/10.1002/ima.22520
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