Threshold values for binary filtering

Question

How to determine good values for the two threshold values for binary filtering?

The images I want to filter are MRI or CT images like these http://pubimage.hcuge.ch:8080/, the images are also most likely gray scale images.

I'm trying to extract a surface model from a stack of 2D images using marching cubes algorithm and binary filtering on the iPad. For the binary filtering I use a lower and upper threshold value, the pixel is set to inside value if lowerThreshold <= pixelValue <= upperThreshold.

Thanks for your help, Manu

Update: I have asked one of my image processing professors about this question now. He said if the histogramm of the image is bimodal (which means there are two hills in the histogramm) the solution is relatively easy which is the case in my images

Answer 1

If your image background is black and your object of interest of any other shade, then you can try to guess a threshold from the histogram of your image (note though, that you may have to try hard to find a suitable percentage threshold that suits all your images).

This may not be sufficient however. A tool that would be interesting for this task is clearly active contours (aka snakes), but it's hard to guess if you can afford the time and effort needed to use them (there is an implementation of geodesic active contours in ITK, but I don't know how much effort it requires before use). If snakes are an option, then you can make the contour evolve from the boundary of your image until they meet your object and fit its contour.