@InProceedings{Supelec617,
author = {Beatrice Chevaillier and Jean-Luc Collette and Damien Mandry and Michel Claudon and Olivier Pietquin},
title = {{Objective assessment of renal DCE-MRI image segmentation}},
year = {2010},
booktitle = {{Proceedings of the European Signal Processing Conference (EUSIPCO 2010)}},
publisher = {Eurasip},
month = {August},
note = {1214-1218},
address = {Aalborg (Denmark)},
url = {http://www.eurasip.org/Proceedings/Eusipco/Eusipco2010/Contents/papers/1569291473.pdf},
isbn = {2076-1465},
abstract = {In dynamic contrast-enhanced magnetic resonance imaging
(DCE-MRI) of renal perfusion with injection of a contrast
agent, the segmentation of kidney in regions of interest
like cortex, medulla and pelvo-caliceal cavities is necessary
for accurate functional evaluation. Several semiautomatic
segmentation methods using time-intensity curves of renal
voxels have been recently developed. Most of the time,
quantitative result validation consists in comparisons with a
manual segmentation by an expert. However it can be questionable
to consider such a segmentation as a ground truth,
especially because of intra- and inter-operator variability.
Moreover it makes comparisons between results published
by different authors delicate. We propose a method to built
synthetic DCE-MRI sequences from typical time-intensity
curves and an anatomical model that can be used for objective
assessment of renal internal structures.}
}