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)
In: Biomedical Signal Processing and Control. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 4(3). ELSEVIER SCI LTD: 247-253.
Konferenzbeitrag
| Veröffentlicht | Englisch
Download
Es wurden keine Dateien hochgeladen. Nur Publikationsnachweis!
Autor*in
Saalbach, Axel;
Lange, Oliver;
Nattkemper, Tim WilhelmUniBi 
;
Meyer-Baese, Anke
;
Meyer-Baese, AnkeEinrichtung
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
Titel des Konferenzbandes
Biomedical Signal Processing and Control
Serien- oder Zeitschriftentitel
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
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. In: Biomedical Signal Processing and Control. BIOMEDICAL SIGNAL PROCESSING AND CONTROL. Vol 4. ELSEVIER SCI LTD; 2009: 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, BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 4, 247-253. ELSEVIER SCI LTD. https://doi.org/10.1016/j.bspc.2009.03.010
Saalbach, Axel, Lange, Oliver, Nattkemper, Tim Wilhelm, and Meyer-Baese, Anke. 2009. “On the application of (topographic) independent and tree-dependent component analysis for the examination of DCE-MRI data”. In Biomedical Signal Processing and Control, 4:247-253. BIOMEDICAL SIGNAL PROCESSING AND CONTROL. ELSEVIER SCI LTD.
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” in Biomedical Signal Processing and Control BIOMEDICAL SIGNAL PROCESSING AND CONTROL, vol. 4, (ELSEVIER SCI LTD), 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. In Biomedical Signal Processing and Control. BIOMEDICAL SIGNAL PROCESSING AND CONTROL. no.4 ELSEVIER SCI LTD, pp. 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, BIOMEDICAL SIGNAL PROCESSING AND CONTROL, vol. 4, ELSEVIER SCI LTD, 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. BIOMEDICAL SIGNAL PROCESSING AND CONTROL. 4, p. 247-253. ELSEVIER SCI LTD (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. ELSEVIER SCI LTD, 2009.Vol. 4. BIOMEDICAL SIGNAL PROCESSING AND CONTROL. 247-253.
3 Zitationen in Europe PMC
Daten bereitgestellt von Europe PubMed Central.
DCT-Based Preprocessing Approach for ICA in Hyperspectral Data Analysis.
Boukhechba K, Wu H, Bazine R., Sensors (Basel) 18(4), 2018
PMID: 29642496
Boukhechba K, Wu H, Bazine R., Sensors (Basel) 18(4), 2018
PMID: 29642496
Standardization of radiological evaluation of dynamic contrast enhanced MRI: application in breast cancer diagnosis.
Furman-Haran E, Feinberg MS, Badikhi D, Eyal E, Zehavi T, Degani H., Technol Cancer Res Treat 13(5), 2014
PMID: 24000989
Furman-Haran E, Feinberg MS, Badikhi D, Eyal E, Zehavi T, Degani H., Technol Cancer Res Treat 13(5), 2014
PMID: 24000989
Classification of vocal aging using parameters extracted from the glottal signal.
Forero Mendoza LA, Cataldo E, Vellasco MM, Silva MA, Apolinário JA., J Voice 28(5), 2014
PMID: 24880675
Forero Mendoza LA, Cataldo E, Vellasco MM, Silva MA, Apolinário JA., J Voice 28(5), 2014
PMID: 24880675
28 References
Daten bereitgestellt von Europe PubMed Central.
Application of magnetic resonance imaging to early detection of breast cancer.
Schnall MD., Breast Cancer Res. 3(1), 2001
PMID: 11300101
Schnall MD., Breast Cancer Res. 3(1), 2001
PMID: 11300101
Dynamic MR imaging of the breast. Analysis of kinetic and morphologic diagnostic criteria.
Szabo BK, Aspelin P, Wiberg MK, Bone B., Acta Radiol 44(4), 2003
PMID: 12846687
Szabo BK, Aspelin P, Wiberg MK, Bone B., Acta Radiol 44(4), 2003
PMID: 12846687
MR imaging of the breast with Gd-DTPA: use and limitations.
Heywang SH, Wolf A, Pruss E, Hilbertz T, Eiermann W, Permanetter W., Radiology 171(1), 1989
PMID: 2648479
Heywang SH, Wolf A, Pruss E, Hilbertz T, Eiermann W, Permanetter W., Radiology 171(1), 1989
PMID: 2648479
Comparison between radiological and artificial neural network diagnosis in clinical screening
Degenhard A, Tanner C, Hayes C, Hawkes DJ, Leach MO., 1999
Degenhard A, Tanner C, Hayes C, Hawkes DJ, Leach MO., 1999
Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions?
Kuhl CK, Mielcareck P, Klaschik S, Leutner C, Wardelmann E, Gieseke J, Schild HH., Radiology 211(1), 1999
PMID: 10189459
Kuhl CK, Mielcareck P, Klaschik S, Leutner C, Wardelmann E, Gieseke J, Schild HH., Radiology 211(1), 1999
PMID: 10189459
Breast fibroadenoma: mapping of pathophysiologic features with three-time-point, contrast-enhanced MR imaging--pilot study.
Weinstein D, Strano S, Cohen P, Fields S, Gomori JM, Degani H., Radiology 210(1), 1999
PMID: 9885614
Weinstein D, Strano S, Cohen P, Fields S, Gomori JM, Degani H., Radiology 210(1), 1999
PMID: 9885614
Neural network-based segmentation of dynamic MR mammographic images
Lucht R, Delorme S, Brix G., 2002
Lucht R, Delorme S, Brix G., 2002
Detection of suspicious lesions in dynamic contrast-enhanced MRI data
Twellmann T, Saalbach A, Mueller C, Nattkemper TW, Wismüller A., 2004
Twellmann T, Saalbach A, Mueller C, Nattkemper TW, Wismüller A., 2004
Visual exploratory analysis of DCE-MRI data in breast cancer by dimensional data reduction: A comparative study
Varini C, Degenhard A, Nattkemper TW., 2006
Varini C, Degenhard A, Nattkemper TW., 2006
Analysis of breast MRI data based on (topographic) independent and tree-dependent component analysis
Saalbach A, Lange O, Nattkemper TW, Meyer-Baese A., 2007
Saalbach A, Lange O, Nattkemper TW, Meyer-Baese A., 2007
Cluster analysis of biomedical image time-series
Wismüller A, Lange O, Dersch DR, Leinsinger GL, Hahn K, Pütz B, Auer D., 2002
Wismüller A, Lange O, Dersch DR, Leinsinger GL, Hahn K, Pütz B, Auer D., 2002
Image fusion for dynamic contrast-enhanced magnetic resonance imaging
Twellmann T, Saalbach A, Gerstung O, Leach MO, Nattkemper TW., 2004
Twellmann T, Saalbach A, Gerstung O, Leach MO, Nattkemper TW., 2004
Independent component analysis for the examination of dynamic contrast-enhanced breast magnetic resonance imaging data: preliminary study.
Yoo SS, Gil Choi B, Han JY, Hee Kim H., Invest Radiol 37(12), 2002
PMID: 12446997
Yoo SS, Gil Choi B, Han JY, Hee Kim H., Invest Radiol 37(12), 2002
PMID: 12446997
Computer-aided diagnosis in breast MRI based on ICA and unsupervised clustering techniques
Meyer-Baese A, Lange O, Wismüller A, Leinsinger G., 2005
Meyer-Baese A, Lange O, Wismüller A, Leinsinger G., 2005
A threshold selection method from gray level histograms
Otsu N., 1979
Otsu N., 1979
Jähne B., 2002
Fast and robust fixed-point algorithms for independent component analysis.
Hyvarinen A., IEEE Trans Neural Netw 10(3), 1999
PMID: 18252563
Hyvarinen A., IEEE Trans Neural Netw 10(3), 1999
PMID: 18252563
Topographic independent component analysis.
Hyvarinen A, Hoyer PO, Inki M., Neural Comput 13(7), 2001
PMID: 11440596
Hyvarinen A, Hoyer PO, Inki M., Neural Comput 13(7), 2001
PMID: 11440596
Finding clusters in independent component analysis
Bach F, Jordan M., 2003
Bach F, Jordan M., 2003
Survey on independent component analysis
Hyvärinen A., 1999
Hyvärinen A., 1999
Independent component analysis of dynamic contrast-enhanced magnetic resonance images of breast carcinoma: a feasibility study.
Koh TS, Thng CH, Ho JT, Tan PH, Rumpel H, Khoo JB., J Magn Reson Imaging 28(1), 2008
PMID: 18421682
Koh TS, Thng CH, Ho JT, Tan PH, Rumpel H, Khoo JB., J Magn Reson Imaging 28(1), 2008
PMID: 18421682
Nattkemper TW, Degenhard A, Twellmann T., 2007
Independent component analysis of fMRI data: examining the assumptions.
McKeown MJ, Sejnowski TJ., Hum Brain Mapp 6(5-6), 1998
PMID: 9788074
McKeown MJ, Sejnowski TJ., Hum Brain Mapp 6(5-6), 1998
PMID: 9788074
Validating the independent components of neuroimaging time series via clustering and visualization.
Himberg J, Hyvarinen A, Esposito F., Neuroimage 22(3), 2004
PMID: 15219593
Himberg J, Hyvarinen A, Esposito F., Neuroimage 22(3), 2004
PMID: 15219593
Spatial and temporal independent component analysis of functional MRI data containing a pair of task-related waveforms.
Calhoun VD, Adali T, Pearlson GD, Pekar JJ., Hum Brain Mapp 13(1), 2001
PMID: 11284046
Calhoun VD, Adali T, Pearlson GD, Pekar JJ., Hum Brain Mapp 13(1), 2001
PMID: 11284046
Unsupervised subpixel target detection for hyperspectral images using projection pursuit
Chiang SS, Chang CI, Ginsberg IW., 2001
Chiang SS, Chang CI, Ginsberg IW., 2001
Egan JP., 1975
Saalbach A., 2006
Export
Markieren/ Markierung löschen
Markierte Publikationen
Web of Science
Dieser Datensatz im Web of Science®Quellen
PMID: 20689662
PubMed | Europe PMC
Suchen in
Google Scholar