Perfusion MRI Deconvolution with Delay Estimation and Non-Negativity Constraints
- Others:
- Computational Imaging of the Central Nervous System (ATHENA) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- Olea Medical [La Ciotat]
- PACA regional council, Olea Medical
Description
Perfusion MRI deconvolution aims to recover the time-dependent residual amount of indicator (residue function) from the measured arterial and tissue concentration time-curves. The deconvolution is complicated by the presence of a time lag between the measured concentrations. Moreover the residue function must be non-negative and its shape may become non-monotonic due to dispersion phenomena. We introduce Modified Exponential Bases (MEB) to perform de-convolution. The MEB generalize the previously proposed exponential approximation (EA) by taking into account the time lag and introducing non-negativity constraints for the recovered residue function also in the case of non-monotonic dispersed shapes, thus overcoming the limitation due to the non-increasing assumtion of the EA. The deconvolution problem is solved linearly. Quantitative comparisons with the widespread block-circulant Singular Value Decomposition show favorable results in recovering the residue function.
Abstract
International audience
Additional details
- URL
- https://hal.inria.fr/hal-01143213
- URN
- urn:oai:HAL:hal-01143213v1
- Origin repository
- UNICA