The best way for selecting a threshold is using the user provided feedback by interactive means.<div><br></div><div>The best you can do is to select the closest threshold to the tumor boundary, usually after </div><div><br>
</div><div>a little trial-and-error the best threshold is identified.</div><div><br></div><div>As Kevin pointed out use the intensity difference between tissues as a cue for the threshold.</div><div><br></div><div>At first start with a large threshold then decrease it till you get the right amount of details in</div>
<div><br></div><div>the segmented image.</div><div><br></div><div>Best regards,</div><div><br></div><div>Dawood</div><div><br></div><div><br></div><div>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>><<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<</div>
<div>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>><<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<</div>
<div><br></div><div><br><div class="gmail_quote">On Mon, Jun 20, 2011 at 8:26 AM, amit satish <span dir="ltr"><<a href="mailto:amitsatish.unde@teamta.in">amitsatish.unde@teamta.in</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
<u></u>
<div bgcolor="#ffffff" text="#000000"><div><div></div><div class="h5">
On 6/18/2011 5:40 PM, Dawood Al Masslawi wrote:
<blockquote type="cite">Hi Amit,
<div><br>
</div>
<div>In addition to what Kevin said, select the Alpha and Beta values
such that the regions you want to </div>
<div><br>
</div>
<div>segment would be emphasized in the resulting image, for an
instance, make the bright regions brighter </div>
<div><br>
</div>
<div>if you want to segment the bright regions.</div>
<div><br>
</div>
<div>Choose the value for Sigma based on how much detail you want to
include in the segmented image, </div>
<div><br>
</div>
<div>lower values will result in more details and higher values will
smooth more details hence resulting in less </div>
<div><br>
</div>
<div>details in the segmented image.</div>
<div><br>
</div>
<div>Assigning the seed points and the threshold by users
(radiologists in your case) can be done using Graphical User Interface </div>
<div><br>
</div>
<div>tools such as FLTK or Qt and VTK, but it's probably better to
get your application up and running before developing a GUI.</div>
<div><br>
</div>
<div>Hope that helps,</div>
<div><br>
</div>
<div>Dawood</div>
<div><br>
</div>
<div><br>
</div>
<div>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>><<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<</div>
<div>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>><<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<br clear="all">
<br>
</div>
<div><br>
<span style="font-family:'Times New Roman';font-size:medium">
<pre>On 06/17/2011 01:39 AM, <a href="http://www.itk.org/mailman/listinfo/insight-users" target="_blank">amitsatish.unde at teamta.in</a> wrote:
><i> I am using ItK fast marching for liver tumor segmentation. I want to select manually seed point and output is segmented tumor. My problems is as below,
</i>><i> 1.can you specify exact value of alpha,beta and sigma for all examples?
</i>><i> <a href="http://2.it" target="_blank">2.it</a>'s very difficult to give threshold value everytime. I am trying to implement a method such that radiologists will choose seed point in tumor region and our algorithm will give exact boundary of tumor. All other parameters i want to set by me.
</i>><i>
</i>><i>
</i>><i> Regards,
</i>><i> Amit
</i>
The parameters used in the software guide for the fast marching
example are listed at the top of the source code :
// Software Guide : BeginCommandLineArgs
// INPUTS: {BrainProtonDensitySlice.png}
// OUTPUTS: {FastMarchingImageFilterOutput5.png}
// 81 114 1.0 -0.5 3.0 100 100
// Software Guide : EndCommandLineArgs
// Software Guide : BeginCommandLineArgs
// INPUTS: {BrainProtonDensitySlice.png}
// OUTPUTS: {FastMarchingImageFilterOutput6.png}
// 99 114 1.0 -0.5 3.0 100 100
// Software Guide : EndCommandLineArgs
// Software Guide : BeginCommandLineArgs
// INPUTS: {BrainProtonDensitySlice.png}
// OUTPUTS: {FastMarchingImageFilterOutput7.png}
// 56 92 1.0 -0.3 2.0 200 100
// Software Guide : EndCommandLineArgs
// Software Guide : BeginCommandLineArgs
// INPUTS: {BrainProtonDensitySlice.png}
// OUTPUTS: {FastMarchingImageFilterOutput8.png}
// OUTPUTS: [FastMarchingFilterOutput1.png]
// OUTPUTS: [FastMarchingFilterOutput2.png]
// OUTPUTS: [FastMarchingFilterOutput3.png]
// 40 90 0.5 -0.3 2.0 200 100
// Software Guide : EndCommandLineArgs
Unfortunately, the parameters are there for a reason, one value
does not always work well for all images.
My advice to you is to take the example programs and to cut them
up into the smallest usable pieces so that you can actually look
at the images at each step. For the fast marching example you'd
end up with 5 tiny programs :
reader -> smoother -> writer
reader -> gradient magnitude -> writer
reader -> sigmoid -> writer
reader -> fast marching -> writer
reader -> threshold -> writer
Take a typical example of your images and open it up in ParaView
(or your viewer of choice).
You'll probably find that the intensity profile through the
object you're interested in is bumpy :
oo
oooooo oo oo
o oo oo o o
oooo ooo oo ooo ooooo oooo
adjust the parameters of the smoothing filter until the profile
looks as much like this as possible:
ooooooooooooo
o o
ooooooooooooooo ooooooooo
adjust the parameters of the gradient magnitude filter until it
looks like this :
o o
o o o o
oooooooooooooo ooooooooooo oooooooo
sigmoid :
ooooooooooooooo oooooooooooooo oooooooooo
o o
fast :
o o
o o
o o
o o
o o
o o
oo
the point is LOOK at the intermediate images.</pre>
</span><br>
</div>
</blockquote></div></div>
Dear Sir,<br>
Thank you for reply. How to choose proper threshold?
Because in my case tumor boundary is not clearly visible.<br>
<br>
<br>
<br>
<br>
Regards,<br>
Amit.<br>
</div>
</blockquote></div><br>
</div>