[Insight-users] Speed of Mutual Information calculation

[Karthik Krishnan]

Markus Weigert wrote:

> Hi Luis,
>
> thanks for your response.
> I use the Viola - Wells implementation.
> Strangely, the Mattes implementation is much faster.

That is strange. Is this for the same number of spatial samples in both 
Viola-Wells and Mattes and for the same number of iterations in both 
cases. I would think *one iteration* of Mattes should be slower than 
*one iteration* of Viola-wells cause of the BSpline based parzen windowing.

> I compiled for release with dbg. information on VC6
> and used GradientDescentOptimizer, not 
> RegularStepGradientDescentOptimizer.
> I plot the progress from a Command Observer and currently don't use 
> multiresolution
> (only on the original resolution).
>
> Cheers,
> Markus
>
>
> ----- Original Message ----- From: "Luis Ibanez" 
> <luis.ibanez at kitware.com>
> To: "Markus Weigert" <m.weigert at fz-juelich.de>
> Cc: <insight-users at itk.org>
> Sent: Monday, May 15, 2006 4:40 PM
> Subject: Re: [Insight-users] Speed of Mutual Information calculation
>
>
>>
>> Hi Markus,
>>
>> Nope, this is not the common time for this size of images.
>>
>> This type of registration should take about 2 minutes in
>> a modern standard computer.
>>
>>
>> Some questions:
>>
>>
>> 1) Are you compiling your application for "Release" ?
>>
>> 2) Are you using multi-resolution ?
>>
>> 3) Are you using the GradientDescent or
>>    the RegularGradientDescent optimizer ?
>>
>> 4) Are you plotting the progress of the optimizer ?
>>    from a connected Command Observer ?
>>
>> 5) Which one of the 5 ITK implementations of
>>    Mutual Information Metric  are you using  ?
>>
>>
>>
>> It is very likely that you are letting the optimizer run
>> for a lot of uncessary iterations.
>>
>> Have you measure the time needed for performing One iteration ?
>> This will indicate if the problem is to have too many iterations,
>> or to have metric evaluations that are too slow.
>>
>>
>>
>> The best way to figure out the problem is to analyze the
>> trace provided by the Command Observer.
>>
>> Given that you are testing with a 3D translation transform,
>> you are in the lucky situation were you can actually plot
>> the path of the optimizer in the parametric space.
>>
>> You could use a tool such as GNUplot, in order to see this
>> path in 3D.  Other easy options are a VTK script, or saving
>> the trace in a .vtk file and loading it into ParaView.
>>
>> Whi
>>
>>
>>
>>
>> =====================
>> Markus Weigert wrote:
>>
>>> Dear insight users,
>>>  I currently try to register two 3D images (CT and MR)
>>> by using mutual information as metric.
>>> The images have a size of approx. 255 * 290 * 75 slices each (MR 
>>> perhaps even more).
>>> Although I use a very simple transformation (translation) and a 
>>> graddescent
>>> optimizer, one iteration of the optimizer takes more than 1.5h.
>>>  Is this a common time for images of this size???
>>> The metric uses 60000 spatial samples.
>>> I thougt about using BSpline transform in the next step of the 
>>> registration
>>> with MI metric too, but I think I can forget to do this, if I have 
>>> to deal with 3000 Parameters
>>> to be optimized!
>>>  Regards,
>>> Markus
>>>  ------------------------------------------------------------------------ 
>>>
>>>
>>> _______________________________________________
>>> Insight-users mailing list
>>> Insight-users at itk.org
>>> http://www.itk.org/mailman/listinfo/insight-users
>>
>>
>>
>
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