Title :
Evaluation of model-independent deconvolution techniques to estimate blood perfusion
Author :
Kind, Taco ; Houtzager, Ivo ; Faes, Theo JC ; Hofman, Mark BM
Author_Institution :
Dept. of Pulmonology, VU Univ. Med. Center, Amsterdam, Netherlands
fDate :
Aug. 31 2010-Sept. 4 2010
Abstract :
This report evaluates several methods to estimate blood perfusion and residue functions in dynamic contrast enhanced (DCE) MRI. Among these are model-dependent and model-independent techniques. All methods were applied to series of Monte Carlo simulations to evaluate the accuracy in order to reproduce different underlying vascular residue functions and blood perfusions. Of the model-independent approaches the use of B-splines with Tikhonov regularization was shown to have a reasonable accuracy in blood perfusion estimations and was less biased than all model-dependent approaches. This technique seems most promising for application to experimental data.
Keywords :
Monte Carlo methods; biomedical MRI; deconvolution; haemorheology; medical image processing; splines (mathematics); B-splines; Monte Carlo simulation; Tikhonov regularization; blood perfusion; dynamic contrast enhanced MRI; model-independent deconvolution technique; vascular residue functions; Accuracy; Autoregressive processes; Blood; Data models; Deconvolution; Signal to noise ratio; Spline; blood flow; deconvolution; magnetic resonance; perfusion; residue function; Algorithms; Computer Simulation; Contrast Media; Humans; Image Enhancement; Linear Models; Magnetic Resonance Imaging; Models, Cardiovascular; Models, Statistical; Monte Carlo Method; Perfusion; Reproducibility of Results; Time Factors;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
Print_ISBN :
978-1-4244-4123-5
DOI :
10.1109/IEMBS.2010.5626615