Brain micro‐vasculature imaging: An unsupervised deep learning algorithm for segmenting mouse brain volume probed by high‐resolution phase‐contrast X‐ray tomography. Issue 3 (15th November 2020)

• Record Type: Journal Article
• Authors: Patera, Alessandra; Zippo, Antonio G.; Bonnin, Anne; Stampanoni, Marco; Biella, Gabriele E. M.
• Is Part Of: International journal of imaging systems and technology. Volume 31:Issue 3(2021)
• Page Start: 1211
• Page End: 1220
• Publication Date: 2020-11-15
• Subjects: brain vasculature system -- deep learning -- X‐ray tomography; Imaging systems -- Periodicals; Image processing -- Periodicals; 621.367
• DOI: 10.1002/ima.22520
• Languages: English
• ISSNs: 0899-9457

Abstract

Abstract: High‐throughput synchrotron‐based tomographic microscopy at third generation 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 demonstrate 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.