Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

NeBSS: Semi-Automated Parcellation of Neonatal Structural Brain MRI

Version 1 : Received: 10 December 2016 / Approved: 10 December 2016 / Online: 10 December 2016 (08:44:55 CET)

How to cite: Ceschin, R.; Zahner, A.; Gopalakrishnan, V.; Panigrahy, A. NeBSS: Semi-Automated Parcellation of Neonatal Structural Brain MRI. Preprints 2016, 2016120060. https://doi.org/10.20944/preprints201612.0060.v1 Ceschin, R.; Zahner, A.; Gopalakrishnan, V.; Panigrahy, A. NeBSS: Semi-Automated Parcellation of Neonatal Structural Brain MRI. Preprints 2016, 2016120060. https://doi.org/10.20944/preprints201612.0060.v1

Abstract

1) Introduction: Brain parcellation is an important processing step in the analysis of structural brain MRI. Existing software implementations are optimized for fully developed adult brains, and provide inadequate results when applied to neonatal brain imaging. 2) Methods: We developed a semi-automated pipeline, NeBSS, for extracting 50 discrete brain structures from neonatal brain MRI, using an atlas registration method that leverages the existing ALBERT neonatal atlas 3) Results: We demonstrate a simple linear workflow for neonatal brain parcellation. NeBSS is robust to variation in imaging acquisition protocol and magnet field strength. 4) Conclusion: NeBSS is a robust pipeline capable of parcellating neonatal brain MRIs using a simple processing workflow. NeBSS fills a need in clinical translational research in neonatal imaging, where existing automated or semi-automated implementations are too rigid to be successfully applied to multi-center neuroprotection studies and clinically heterogeneous cohorts. The software is open source and freely available.

Keywords

neonatal MRI; brain structure segmentation; volume extraction

Subject

Computer Science and Mathematics, Software

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.