Different Metric Mappings

The following plots show different ways that I mapped the metric into different mathematical functions. This was done by mapping all the metric values for a square surrounding the center of the brain MRI image to statistical function. The first is a Gaussian with narrow standard deviation.

The second is a Gaussian with a wider standard deviation. Just the first half of a Gaussian was used so the left hand tail up to the peak, meaning is the standard deviation is wider then there is less of a peak and therefore a greater range of mapped values for metric results with low values. Also, a lower metric value is better and means the ellipse has a better fit onto the skull.

The final plot is a mapping to a Sigmoid function that grows very steeply.