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Mohajer, M. ; Brix, G. ; Englmeier, K.-H.

A novel and fast method for cluster analysis of DCE-MR image series of breast tumors.

Proc. SPIE 7626:76260R (2010)
Verlagsversion DOI
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
A novel approach is introduced for clustering tumor regions with similar signal-time series measured by dynamic contrast-enhanced (DCE) MRI to segment the tumor area in breast cancer. Each voxel of the DCE-MRI dataset is characterized by a signal-time curve. The clustering process uses two describer values for each pixel. The first value is L2-norm of each time series. The second value r is calculated as sum of differences between each pair of S(n-i) and S(i) for i = {0...n/2} where S is the intensity and n the number of values in a time series. We call r reverse value of a time series. Each time series is considered as a vector in an n-dimensional space and the L2-norm and reverse value of a vector are used as similarity measures. The curves with similar L2-norms and similar reverse values are clustered together. The method is tested on breast cancer DCE-MRI datasets with N = 256 x 256 spatial resolution and n = 128 temporal resolution. The quality of each cluster is described through the variance of Euclidean distances of the vectors to the mean vector of the corresponding cluster. The combination of both similarity measures improves the segmentation compared to using each measure alone.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Herausgeber Molthen, R.C.* ; Weaver, J.B.*
Schlagwörter DCE-MRI; Time Series; Segmentation; Clustering; Lp-norm
Sprache englisch
Veröffentlichungsjahr 2010
HGF-Berichtsjahr 0
ISSN (print) / ISBN 0277-786X
e-ISSN 1996-756X
Konferenztitel SPIE Medical Imaging
Konferzenzdatum 13-18 February 2010
Konferenzort San Diego, USA
Zeitschrift Proceedings of SPIE
Quellenangaben Band: 7626, Heft: , Seiten: , Artikelnummer: 76260R Supplement: ,
Verlag SPIE
Verlagsort Bellingham, WA
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Biological and Medical Imaging (IBMI)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-505500-003
DOI 10.1117/12.843967
Scopus ID 77953303156
Erfassungsdatum 2010-07-15
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