Publication Type |
Journal Article |
School or College |
College of Engineering |
Department |
Electrical & Computer Engineering |
Creator |
Tasdizen, Tolga; Terry, Christi M.; Cheung, Alfred K.; Kirby, Robert Michael II |
Other Author |
Preston, J. Samuel |
Title |
Using the stochastic collocation method for the uncertainty quantification of drug concentration due to depot shape variability |
Date |
2009 |
Description |
Numerical simulations entail modeling assumptions that impact outcomes. Therefore, characterizing, in a probabilistic sense, the relationship between the variability of model selection and the variability of outcomes is important. Under certain assumptions, the stochastic collocation method offers a computationally feasible alternative to traditional Monte Carlo approaches for assessing the impact of model and parameter variability. We propose a framework that combines component shape parameterization with the stochastic collocation method to study the effect of drug depot shape variability on the outcome of drug diffusion simulations in a porcine model. We use realistic geometries segmented from MR images and employ level-set techniques to create two alternative univariate shape parameterizations. We demonstrate that once the underlying stochastic process is characterized, quantification of the introduced variability is quite straightforward and provides an important step in the validation and verification process. |
Type |
Text |
Publisher |
Institute of Electrical and Electronics Engineers (IEEE) |
Volume |
56 |
Issue |
3 |
First Page |
609 |
Last Page |
620 |
Language |
eng |
Bibliographic Citation |
Preston, J. S., Tasdizen, T., Terry, C. M., Cheung A. K., & Kirby, R. M. II. (2009). Using the stochastic collocation method for the uncertainty quantification of drug concentration due to depot shape variability. IEEE Transactions on Biomedical Engineering, 56(3), 609-20. March. |
Rights Management |
(c) 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
Format Medium |
application/pdf |
Format Extent |
985,791 bytes |
Identifier |
ir-main,15200 |
ARK |
ark:/87278/s6wd4j2r |
Setname |
ir_uspace |
ID |
706037 |
Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6wd4j2r |