[Insight-users] muliple pahse Chan Vese, one partition totally shrink

Baoyun Li baoyun_li123 at yahoo.com
Fri Mar 26 15:37:47 EDT 2010


Dear All:
 
I believed that Arnaud is right. In my case, the objects are not distcted each other.
 
Also, kishore, how should I used itkChenAndVese filter if my inputs are vector images. As I understand, this filter doesnot surpport vector image as input. 
 
Thanks
 
Baoyun
--- On Fri, 3/26/10, Arnaud GELAS <arnaud_gelas at hms.harvard.edu> wrote:


From: Arnaud GELAS <arnaud_gelas at hms.harvard.edu>
Subject: Re: [Insight-users] muliple pahse Chan Vese, one partition totally shrink
To: "Kishore Mosaliganti" <kishoreraom at gmail.com>
Cc: "Baoyun Li" <baoyun_li123 at yahoo.com>, "insight-users at itk.org" <insight-users at itk.org>, "Luis Ibanez" <luis.ibanez at kitware.com>
Date: Friday, March 26, 2010, 6:26 PM


Just a comment regarding the kd-tree optimization, this will work only if considered objects are really distinct. (One object must not contain another one).
But if I correctly understood what you want to do, this should not apply to your case...

On 03/26/2010 01:25 PM, Kishore Mosaliganti wrote: 
Hi Baoyun,

You are right that if you set 4 phases in the levelset, then no phase will shrink to empty.

In ITK, if you use the classes on ScalarChanAndVeseLevelSetImageFilter, you can separately encode the 3 regions in 3 separate level-set functions and these functions compete with each other for the segmentations at the boundaries. You can also control each level-set parameters separately. 

If you have N objects, then you can make use of a built-in kd-tree optimization that speeds up the approach. Each levelset function is only defined in a small subdomain containing your object instead of the whole image thereby saving space.


Kishore


On Fri, Mar 26, 2010 at 10:48 AM, Baoyun Li <baoyun_li123 at yahoo.com> wrote:






Dear All:
 
Thanks for your reply, now seems I undertand the question more.
 
According to Wanlin's paper, I need to encoding the 2 level set to  3 phase if I want to 3 segmenations. If I need 4  segmentation, I need to encode the levelset to 4 phases.
 
So my origianl question is not correct, once I set 4 phases, no phase will shrink to empty, and I will get 4 segmentation anyway. (Please correct me if I am wrong).
 
Thanks and my best regards
 
Baoyun
 
Please correct me if I am wrong

--- On Thu, 3/25/10, Luis Ibanez <luis.ibanez at kitware.com> wrote:


From: Luis Ibanez <luis.ibanez at kitware.com> 

Subject: Re: [Insight-users] muliple pahse Chan Vese, one partition totally shrink
To: "Baoyun Li" <baoyun_li123 at yahoo.com>
Cc: insight-users at itk.org, "Mosaliganti, Kishore Rao" <Kishore_Mosaliganti at hms.harvard.edu>
Date: Thursday, March 25, 2010, 10:43 PM 





Hi Baoyun,


You seem to be mixing two different issues here.

One thing is to segment the image in different regions,
and a separate issue is to find an efficient encoding 
for the resulting segmentations.


If you want to segment three different anatomical structures
from your image, then you want to use a level set with 
three phases.

That is, one phase per object to be segmented.


      Regards,


            Luis


-----------------------------------------------------------------------------

On Wed, Mar 24, 2010 at 5:52 PM, Baoyun Li <baoyun_li123 at yahoo.com> wrote:






Dear All:
 
I have a theoritical question about Chen Vese multiplse pahse leve set.
 
I have two level set and the two level set can segment the image to 4 segments, then I can calculate the mean for each segments as following
 
%c11 = mean (phi1>0 & phi2>0)
%c12 = mean (phi1>0 & phi2<0)
%c21 = mean (phi1<0 & phi2>0)
%c22 = mean (phi1<0 & phi2<0)
 
How about if I only have three segments, let say segment (phi1<0 & phi2<0) will finally shrink to zeros.
 
Then how to I calcuate c22, and also what value of c22 I should use to update leve set equation as shown below:
 
((u-c22)^2-(u-c12)^2)H(phi2).
 
I saw somebody use the mininum number of the machine to replace c22, but I could not imagine what will happen and why to do that.
 
Thanks
Baoyun
 
 
 
 
 

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