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
Smith, S.M., Zhang, Y., Jenkinson, M., Chen, J., Matthews, P.M., Federico, A., et al. (2002). Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. NEUROIMAGE, 17(1), 479-489 [10.1006/nimg.2002.1040].
Accurate, robust, and automated longitudinal and cross-sectional brain change analysis
FEDERICO A.;DE STEFANO N.
2002-01-01
Abstract
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 estimationFile | Dimensione | Formato | |
---|---|---|---|
smith.pdf
non disponibili
Tipologia:
Post-print
Licenza:
NON PUBBLICO - Accesso privato/ristretto
Dimensione
296.15 kB
Formato
Adobe PDF
|
296.15 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11365/20367
Attenzione
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo