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Exploring the discrimination power of the time domain for segmentation and characterization of active lesions in serial MR data (1998)
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BibTeX
@MISC{Gerig98exploringthe,
author = {Guido Gerig and Daniel Welti and Charles R. G. Guttmann and Alan C. F. Colchester and Gábor Székely},
title = {Exploring the discrimination power of the time domain for segmentation and characterization of active lesions in serial MR data},
year = {1998}
}
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Abstract
This paper presents a new method for the automatic segmentation and characterization of object changes in time series of three-dimensional data sets. The technique was inspired by procedures developed for analysis of functional MRI data sets. After precise registration of serial volume data sets to 4-D data, we applied a time series analysis taking into account the characteristic time function of variable lesions. The images were preprocessed with a correction of image field inhomogeneities and a normalization of the brightness over the whole time series. Thus, static regions remain unchanged over time, whereas changes in tissue characteristics produce typical intensity variations in the voxel's time series. A set of features was derived from the time series, expressing probabilities for membership to the sought structures. These multiple sources of uncertain evidence were combined to a single evidence value using Dempster Shafer's theory. The project was driven by the object...
Keyphrases
discrimination power active lesion time series serial mr data time domain new method whereas change 4-d data typical intensity variation multiple source three-dimensional data set characteristic time function functional mri data set precise registration sought structure object change dempster shafer single evidence value serial volume data set image field inhomogeneity tissue characteristic automatic segmentation whole time series static region time series analysis variable lesion uncertain evidence
