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.}