Variational Physiologically Informed Solution to Hemodynamic and Perfusion Response Estimation from ASL fMRI Data

Aina Frau-Pascual (1, 2) , Florence Forbes (1) , Philippe Ciuciu (3, 2)

1 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
2 PARIETAL - Modelling brain structure, function and variability based on high-field MRI data
3 CEA - Commissariat à l'énergie atomique et aux énergies alternatives

Functional Arterial Spin Labeling (fASL) MRI can provide a quantitative measurement of cerebral blood flow. A joint detection-estimation (JDE) framework has been considered to extract task-related perfusion and hemodynamic responses not restricted to canonical response function shapes. In this work, we provide a variational expectation-maximization (VEM) algorithm for hemodynamic and perfusion responses estimation. This approach provides a lower computational load compared to previous attempts, and facilitates the incorporation of prior knowledge and constraints in the estimation. Validation on simulated and real data sets has been performed.

Domaines: Statistiques [math.ST]; Imagerie

Aina Frau-Pascual, Florence Forbes, Philippe Ciuciu. Variational Physiologically Informed Solution to Hemodynamic and Perfusion Response Estimation from ASL fMRI Data. 2015 International Workshop on Pattern Recognition in NeuroImaging, Jun 2015, Stanford, CA, United States. pp.57-60, ⟨10.1109/PRNI.2015.12⟩. ⟨hal-01249015⟩