Antw: [Insight-users] Shape prior level sets: question about MAPCostFunction

[Quan Chen]

>I decided that for my work, I would prefer to change the definition of 
>the inside term from Leventon's work. He states that P(current curve | 
>estimated shape) is inversely proportional to the volume of the current 
>curve outside the estimated shape. This is just one possible model for 
>that probability. I noticed that both the evolving curve and the 
>estimated shape are signed distance functions, so they can be directly 
>compared. As such, I use the L1-norm of the difference between these 
>functions (in the narrow band active region) as a similarity metric, 
>and use that as a proxy for the probability. L2 and L-infinity norms 
>(RMSD and maximum deviation) seem good too. In this way, I encourage 
>the shape model to "stay near" the evolving curve. This is bad when the 
>curve is very small compared to its desired final size, however -- in 
>these regimes Leventon's initial suggestion is better. I am examining 
>ways to switch between the two probability definitions based on the 
>size of the curve.

Seems you are using some measure similiar to directed Hausdorff
distance, how about use UN-directed Hausdorff distance?