✦ LIBER ✦

Bayesian wavelet-based analysis of functional magnetic resonance time series

✍ Scribed by Sergi G. Costafreda; Gareth J. Barker; Michael J. Brammer

Publisher: Elsevier Science
Year: 2009
Tongue: English
Weight: 413 KB
Volume: 27
Category: Article
ISSN: 0730-725X
DOI: 10.1016/j.mri.2008.09.001

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Multidimensional wavelet analysis of fun

Multidimensional wavelet analysis of functional magnetic resonance images

✍ Michael J. Brammer 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 174 KB 👁 2 views

Analysis of functional magnetic resonance imaging (fMRI) data requires the application of techniques that are able to identify small signal changes against a noisy background. Many of the most commonly used methods cannot deal with responses which change amplitude in a fashion that cannot easily be

Time series analysis in the time domain

Time series analysis in the time domain and resampling methods for studies of functional magnetic resonance brain imaging

✍ Joseph J. Locascio; Peggy J. Jennings; Christopher I. Moore; Suzanne Corkin 📂 Article 📅 1997 🏛 John Wiley and Sons 🌐 English ⚖ 502 KB

Although functional magnetic resonance imaging (fMRI) methods yield rich temporal and spatial data for even a single subject, universally accepted data analysis techniques have not been developed that use all the potential information from fMRI of the brain. Specifically, temporal correlations and c

Cardiovascular magnetic resonance evalua

Cardiovascular magnetic resonance evaluation for left ventricular diastolic function: analysis of time-volume curve

✍ Takashi Tanimoto; Keizo Kimura; Shingo Ota; Tomizo Masuno; Yuichi Ozaki; Kumiko 📂 Article 📅 2012 🏛 BioMed Central 🌐 English ⚖ 78 KB

Large sample group independent component

Large sample group independent component analysis of functional magnetic resonance imaging using anatomical atlas-based reduction and bootstrapped clustering

✍ Ariana Anderson; Jennifer Bramen; Pamela K. Douglas; Agatha Lenartowicz; Andrew 📂 Article 📅 2011 🏛 John Wiley and Sons 🌐 English ⚖ 257 KB

## Abstract Independent component analysis (ICA) is a popular method for the analysis of functional magnetic resonance imaging (fMRI) signals that is capable of revealing connected brain systems of functional significance. To be computationally tractable, estimating the independent components (ICs)

Depth sensitivity analysis of functional

Depth sensitivity analysis of functional near-infrared spectroscopy measurement using three-dimensional Monte Carlo modelling-based magnetic resonance imaging

✍ Chemseddine Mansouri; Jean-Pierre L’Huillier; Nasser H. Kashou; Anne Humeau 📂 Article 📅 2010 🏛 Springer-Verlag 🌐 English ⚖ 246 KB

Time-Domain Quantification of Amplitude,

Time-Domain Quantification of Amplitude, Chemical Shift, Apparent Relaxation TimeT*2, and Phase by Wavelet-Transform Analysis. Application to Biomedical Magnetic Resonance Spectroscopy

✍ Hacene Serrai; Lotfi Senhadji; Jacques D. de Certaines; Jean Louis Coatrieux 📂 Article 📅 1997 🏛 Elsevier Science 🌐 English ⚖ 313 KB

The wavelet-transform method is used to quantify the magnetic resonance spectroscopy (MRS) parameters: chemical shift, apparent relaxation time T2, resonance amplitude, and phase. Wavelet transformation is a time-frequency representation which separates each component from the FID, then successively