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

Mojgan Mohajer; Gunnar Brix; Karl-Hans Englmeier

doi:10.1117/12.843967

9 March 2010 A novel and fast method for cluster analysis of DCE-MR image series of breast tumors

Mojgan Mohajer, Gunnar Brix, Karl-Hans Englmeier

Proceedings Volume 7626, Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging; 76260R (2010) https://doi.org/10.1117/12.843967
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

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.

Citation Download Citation

Mojgan Mohajer, Gunnar Brix, and Karl-Hans Englmeier "A novel and fast method for cluster analysis of DCE-MR image series of breast tumors", Proc. SPIE 7626, Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging, 76260R (9 March 2010); https://doi.org/10.1117/12.843967

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available