On the application of (topographic) independent and tree-dependent component analysis for the examination of DCE-MRI data

Saalbach A, Lange O, Nattkemper TW, Meyer-Baese A (2009)
BIOMEDICAL SIGNAL PROCESSING AND CONTROL 4(3): 247-253.

Konferenzbeitrag | Veröffentlicht | Englisch
 
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Abstract / Bemerkung
In this contribution we investigate the applicability of different methods from the field of independent component analysis (ICA) for the examination of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data from breast cancer research. DCE-MRI has evolved in recent years as a powerful complement to X-ray based mammography for breast cancer diagnosis and monitoring. In DCE-MRI the time related development of the signal intensity after the administration of a contrast agent can provide valuable information about tissue states and characteristics. To this end, techniques related to ICA, offer promising options for data integration and feature extraction at voxel level. In order to evaluate the applicability of ICA, topographic ICA and tree-dependent component analysis (TCA), these methods are applied to twelve clinical cases from breast cancer research with a histopathologically confirmed diagnosis. For ICA these experiments are complemented by a reliability analysis of the estimated components. The outcome of all algorithms is quantitatively evaluated by means of receiver operating characteristics (ROC) statistics whereas the results for specific data sets are discussed exemplarily in terms of reification, score-plots and score images. (C) 2009 Elsevier Ltd. All rights reserved.
Stichworte
(Topographic) independent component analysis; DCE-MRI; Tree-dependent; component analysis; Breast cancer research
Erscheinungsjahr
2009
Band
4
Ausgabe
3
Seite(n)
247-253
ISSN
1746-8094
Page URI
https://pub.uni-bielefeld.de/record/1591448

Zitieren

Saalbach A, Lange O, Nattkemper TW, Meyer-Baese A. On the application of (topographic) independent and tree-dependent component analysis for the examination of DCE-MRI data. BIOMEDICAL SIGNAL PROCESSING AND CONTROL. 2009;4(3):247-253.
Saalbach, A., Lange, O., Nattkemper, T. W., & Meyer-Baese, A. (2009). On the application of (topographic) independent and tree-dependent component analysis for the examination of DCE-MRI data. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 4(3), 247-253. doi:10.1016/j.bspc.2009.03.010
Saalbach, A., Lange, O., Nattkemper, T. W., and Meyer-Baese, A. (2009). On the application of (topographic) independent and tree-dependent component analysis for the examination of DCE-MRI data. BIOMEDICAL SIGNAL PROCESSING AND CONTROL 4, 247-253.
Saalbach, A., et al., 2009. On the application of (topographic) independent and tree-dependent component analysis for the examination of DCE-MRI data. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 4(3), p 247-253.
A. Saalbach, et al., “On the application of (topographic) independent and tree-dependent component analysis for the examination of DCE-MRI data”, BIOMEDICAL SIGNAL PROCESSING AND CONTROL, vol. 4, 2009, pp. 247-253.
Saalbach, A., Lange, O., Nattkemper, T.W., Meyer-Baese, A.: On the application of (topographic) independent and tree-dependent component analysis for the examination of DCE-MRI data. BIOMEDICAL SIGNAL PROCESSING AND CONTROL. 4, 247-253 (2009).
Saalbach, Axel, Lange, Oliver, Nattkemper, Tim Wilhelm, and Meyer-Baese, Anke. “On the application of (topographic) independent and tree-dependent component analysis for the examination of DCE-MRI data”. BIOMEDICAL SIGNAL PROCESSING AND CONTROL 4.3 (2009): 247-253.

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