Abstract

The method described has been shown to be accurate ( approximately 0.2% brain volume change error) and to achieve high robustness (no failures in several hundred analyses over a range of different data sets).

Keywords

Robustness (evolution)SkewArtificial intelligenceMedicineComputer visionAutomationComputer science

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Publication Info

Year
2001
Type
article
Volume
25
Issue
3
Pages
466-475
Citations
491
Access
Closed

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Cite This

Stephen M. Smith, Nicola De Stefano, Mark Jenkinson et al. (2001). Normalized Accurate Measurement of Longitudinal Brain Change. Journal of Computer Assisted Tomography , 25 (3) , 466-475. https://doi.org/10.1097/00004728-200105000-00022

Identifiers

DOI
10.1097/00004728-200105000-00022