Quantitative measurement of brain size, shape, and temporal change (for example, in order to estimate atrophy) is increasingly important in biomedical image analysis applications. New methods of structural analysis attempt to improve robustness, accuracy, and extent of automation. A fully automated method of longitudinal (temporal change) analysis, SIENA, was presented previously. In this paper, improvements to this method are described, and also an extension of SIENA to a new method for cross-sectional (single time point) analysis. The methods are fully automated, robust, and accurate: 0.15% brain volume change error (longitudinal): 0.5-1% brain volume accuracy for single-time point (cross-sectional). A particular advantage is the relative insensitivity to differences in scanning parameters. The methods provide easy manual review of their output by the automatic production of summary images which show the results of the brain extraction, registration, tissue segmentation, and final atrophy estimation.

Original publication

DOI

10.1006/nimg.2002.1040

Type

Journal article

Journal

NeuroImage

Publication Date

09/2002

Volume

17

Pages

479 - 489

Addresses

Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Department of Clinical Neurology, FMRIB, University of Oxford, John Radcliffe Hospital, Headley Way, Headington, Oxford, United Kingdom.

Keywords

Skull, Brain, Frontal Lobe, Humans, Epilepsy, Atrophy, Magnetic Resonance Imaging, Neurosurgical Procedures, Longitudinal Studies, Cross-Sectional Studies, Reproducibility of Results, Algorithms, Time Factors, Image Processing, Computer-Assisted