[Insight-users] polynomial fitting for fcMRI processing

[Karen Guan]

Hi Luis,

Thanks very much for the answer and the reference! However, after the manual
of itk::MultivariateLegendrePolynomial seems to suggest that this function
works only for 2D and 3D data. Although it's possible to add one dummy
dimension (eg. all zero), I'm wondering whether there's a function more
suitable for 1D signal.

Best,
- Karen

On 6/6/07, Luis Ibanez <luis.ibanez at kitware.com> wrote:
>
>
> Hi Karen,
>
>
> You can use the Multivariate Legendre Polynomials,
> and combine them with the Linear Kalman estimator,
> or with the Levenberg-Marquard optimizer.
>
>
> http://www.itk.org/Insight/Doxygen/html/classitk_1_1MultivariateLegendrePolynomial.html
>
> http://www.itk.org/Insight/Doxygen/html/classitk_1_1KalmanLinearEstimator.html
>
> http://www.itk.org/Insight/Doxygen/html/classitk_1_1LevenbergMarquardtOptimizer.html
>
>
> In both cases you will be using the sum of squared
> differences between your data and the polynomial,
> as the metric to minimize.
>
>
> Please look at the recent trail by Mathieu Malaterre
> on this topic in the users list.
>
>
>
>     Regards,
>
>
>        Luis
>
>
> --------------------
> Karen Guan wrote:
> > Dear all,
> >
> > I'm working on fcMRI processing, and need polynomial fitting (3rd order,
> > ax^3 + bx^2 + cx +d) for each time course (with about 600 time points)
> > to remove B0 fluctuation or shifting. The entire data set
> > has 128 * 128 * 7 samples ( i.e. time courses).
> >
> > The questions are:
> > 1. Is there such an algorithm in ITK (including vnl/vcl)?
> > 2. If so, for fast processing of 1-D signal with 600 samples, what are
> > be best choices?
> >
> > I appreciate the help!
> >
> > - X.
> >
> >
> >
> > ------------------------------------------------------------------------
> >
> > _______________________________________________
> > Insight-users mailing list
> > Insight-users at itk.org
> > http://www.itk.org/mailman/listinfo/insight-users
>
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