Journal article
Robust Estimation of HDR in fMRI using H-infinity Filters
Estimation and detection of the hemodynamic response (HDR) are of great importance in functional MRI (fMRI) data analysis. In this paper, we propose the use of three H-infinity adaptive filters (finite memory, exponentially weighted, and timevarying) for accurate estimation and detection of the HDR.
The H8 approach is used because it safeguards against the worst case disturbances and makes no assumptions on the (statistical) nature of the signals [B. Hassibi and T. Kailath, in Proc. ICASSP, 1995, vol. 2, pp. 949-952; T. Ratnarajah and S. Puthusserypady, in Proc. 8th IEEEWorkshopDSP, 1998, pp. 1483-1487].
Performances of the proposed techniques are compared to the conventional t-test method as well as the well-known LMSs and recursive least squares algorithms. Extensive numerical simulations show that the proposed methods result in better HDR estimations and activation detections.
| Language: | English |
|---|---|
| Publisher: | IEEE |
| Year: | 2010 |
| Pages: | 1133-1142 |
| ISSN: | 15582531 and 00189294 |
| Types: | Journal article |
| DOI: | 10.1109/TBME.2009.2039569 |
| ORCIDs: | Puthusserypady, Sadasivan |
<formula formulatype="inline"><tex Notation="TeX">$H^\infty$</tex></formula> filters Algorithms Brain Brain Mapping Data analysis Evoked Potentials H<sup>∞</sup> adaptive filter HDR estimation Hemodynamics Humans Image Interpretation, Computer-Assisted Intersymbol interference Magnetic Resonance Imaging Magnetic resonance imaging Nonlinear filters Oxygen Oxygen Consumption Robustness Shape Signal design adaptive filters biomedical MRI fMRI functional magnetic resonance imaging haemodynamics hemodynamic response least squares approximations medical signal processing recursive least squares algorithm
