Dental X-ray : Help watershed oversegmentation

[pateheo]

Hi everybody,

I'm doing dental x-ray segmentation. My objective is locate and
extract teeth from x-ray film. Any body sees a x-ray film ? It
contains 2-4 teeth each jaw or both jaws. After thresholding, I use
watershed on binary image to separate each teeth. But watershed does
oversegmentation on image. So, a tooth is segmented into 2, 3, 4 or 5
pieces. Now I want group them correctly : pieces that belong to a
tooth will group together, not pieces of other teeth. Some figures
at:

http://www.flickr.com/photos/58759896@N00/sets/72157600230584771/

I do not use the watershed segmentation on grayscale image because it
is too oversegmentation and my process must be automatic completely.
It implies that I can't use markers. In case of using markers, I think
it can't gain good performance because the brightness of tooth varies
strong.

I've tried some methods to group those pieces such as topological
attributes of shapes and hierachical clustering but don't know how to
use them.

Anybody could help me?
Thanks in advance.

Phong

[Pixel.to.life]

Phong,

Let me first warn you: you might be able to use a simple technique. So
yu may first try snakes for example, then if that doesnt work, you may
think of experimenting with levelsets.

Now, the answers

[1] Yes you can apply level set based segmentation to a single image.
It does not have to be 3D image set.

[2] http://math.berkeley.edu/~sethian/2006/Explanations/interface_explain.html

[3] Plain thresholding or image intensity based methods lack any
information about shape in the image. Snakes or active contours track
a set of connected markers, but can become complicated when the shape
of the target object changes topology when growing (e.g. near sharp
corners or fold-overs). There could also be diffifculties using them
in higher dimensions. Level set based segmentation also tracks moving
interfaces, but approaches teh problem using the link between moving
interfaces and equations from computational fluid equations. The
advantages are manifold: the formulations are highly stable, accurate,
and preserve monotonicity, as well as deal with changes in topology.

[4] Yes you can embed a prior shape within a level set formulation.
Here is an example: http://citeseer.ist.psu.edu/656264.html

Good luck,

>>>>>>>>>>

Firstly, Thanks to pixel.to.life !

Secondly, I have some question to ask you :)). Could you give some
advantage of level set method compared to traditional method :
threshold, snake and watershed?

Level set method is approriate to a series of images. My input is a
single image, may I use Level set effectively ?

Can we embedded prior shape into level set method ?

Thanks you very much

Have a good day

Phong