A 3-D spatio-temporal deconvolution approach for MR perfusion in the brain

Carole Frindel, Marc C. Robini, David Rousseau

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

We propose an original spatio-temporal deconvolution approach for perfusion-weighted MRI applied to cerebral ischemia. The regularization of the underlying inverse problem is achieved with spatio-temporal priors and the resulting optimization problem is solved by half-quadratic minimization. Our approach offers strong convergence guarantees, including when the spatial priors are non-convex. Moreover, experiments on synthetic data and on real data collected from subjects with ischemic stroke show significant performance improvements over the standard approaches-namely, temporal deconvolution based on either truncated singular-value decomposition or ℓ2-regularization-in terms of various performance measures.

Original languageEnglish
Pages (from-to)144-160
Number of pages17
JournalMedical Image Analysis
Volume18
Issue number1
DOIs
Publication statusPublished - 2014 Jan
Externally publishedYes

Keywords

  • Acute stroke
  • Deconvolution
  • Perfusion weighted MRI
  • Spatio-temporal model
  • Tissue outcome prediction

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

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