Image Fitting - Speeding Up Fitting
In certain situations, for example to avoid fitting to background noise, it may be useful to
exclude some pixels from the fitting procedure. There are four ways to exclude (mask out) pixels:
These are:
- to
exclude pixels based on their intensity, enter an intensity threshold. If all the
pixels at one position in the input images are above the threshold, fitting is performed for
that pixel as normal.
- use
the Brain Finder exclude pixels outside the brain. If you are
analysing human brain images, it may be possible to use the Brain
Finder tool to first isolate the brain, and then fit to pixels only inside the brain.
The Brain Finder will be applied to the first image in your series with different independent
variable values, so the success of this depends on whether it has a contrast suitable for use
with Brain Finder. To use this, enter
a "Threshold
fraction" that has previously been found to be suitable for your image (by experimenting
with the Brain Finder).
- to use another
image to exclude pixels from fitting. An image mask in an image with the same number of
columns, rows and slices of pixels as the images being analysed. For pixels to be fitted, the
image mask's pixel intensity is non-zero, and for pixels that are to be excluded from fitting,
the image mask's pixel intensity is zero.
- to use a set of
regions-of-interest (ROIs) exclude pixels from fitting. The ROIs are defined on one of the
input images. Pixels outside the ROIs are not fitted.
When fitting is not performed in a particular pixel because that pixel is excluded by the masking
operation, the intensity in all the output images set to zero for that pixel. This can speed up
the fitting considerably. It also make the output images look prettier by excluding the random
values output when fitting to noise.