DocumentCode
2928461
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
fYear
2010
fDate
Aug. 31 2010-Sept. 4 2010
Firstpage
2602
Lastpage
2607
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location
Buenos Aires
ISSN
1557-170X
Print_ISBN
978-1-4244-4123-5
Type
conf
DOI
10.1109/IEMBS.2010.5626615
Filename
5626615
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