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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)
Publ. Version/Full Text DOI
Open Access Green as soon as Postprint is submitted to ZB.
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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Publication type Article: Journal article
Document type Scientific Article
Editors Molthen, R.C.* ; Weaver, J.B.*
Corresponding Author
Keywords DCE-MRI; Time Series; Segmentation; Clustering; Lp-norm
ISSN (print) / ISBN 0277-786X
e-ISSN 1996-756X
Conference Title SPIE Medical Imaging
Conference Date 13-18 February 2010
Conference Location San Diego, USA
Journal Proceedings of SPIE
Quellenangaben Volume: 7626, Issue: , Pages: , Article Number: 76260R Supplement: ,
Publisher SPIE
Publishing Place Bellingham, WA
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Biological and Medical Imaging (IBMI)