<div>Hi itk users,</div>
<div> </div>
<div>I'm trying to identify the external boundaries of an object that </div>
<div>is placed on a very noisy background.</div>
<div> </div>
<div>The approach I would like to follow (and that I implemented) </div>
<div>involves the application of the levelset geodesic active countour </div>
<div>method initialized outside of the object self and then make the </div>
<div>algorithm to evolve not expanding the front but contracting it in order</div>
<div>to stick on the object edges</div>
<div> </div>
<div>My approach then involves then the following steps</div>
<div>-1)I Use a combination of gradiend extraction filter followed by a sigmoid</div>
<div> filter to extract the the external object boundaries and put</div>
<div> this data as FeatureImage of the levelset filter. The result is </div>
<div> an image with low values near the object borders and high values</div>
<div> in other places.</div>
<div>-2) Instead of using the fastmarching algorithm to create the initial</div>
<div> levelset solution I filled the initial image with two nested quads. </div>
<div> The outer quad, that doesn't intersect the object, but intersects only</div>
<div> the background, has value equal to 0.5. The inner quad that is </div>
<div> covering the object has values equal to -0.5. What I expect to</div>
<div> have is the high value quad to contract filling the low value area.</div>
<div> As soon as the object boundaries are detected the expansion of </div>
<div> the high value area should stop and applying the thresholding filter </div>
<div> should result in the background and the object external boundaries.</div>
<div>-3) According the itk code I gave to the propagation a negative value since</div>
<div> I want a front contraction.</div>
<div> </div>
<div>My problems are due to the fact that the algorithm doesn't evolve as expected.</div>
<div>After a lot of iterations (18000 for an image 1280 x 960) the white border has covered</div>
<div><span></span>all the image and no object is visible. I even tried to change the propagation sign and value</div>
<div>but without any luck.</div>
<div>The strange thing is that if I create an initial levelset surface with value equal to -0.5 inside </div>
<div>a small quad and value 0.5 over the resulting image with positive propagation the algorithm</div>
<div>evolves identifying some edges.</div>
<div>So my questions are:</div>
<div>-) Could you please give me any advice about my troubles ?</div>
<div>-) Do you think the method is correct or you can see any other better method</div>
<div> </div>
<div>Thanks in advance for reading and for any help</div>
<div>Regards </div><span class="sg">
<div>-Loris Vosilla</div></span>