[Insight-users] Registration Algo

[V Narasinga Rao]

Hi Luis,

Thanks for the Mail, well what i meant abt. application was that it's not 
defined throughly. I have done registration for CT-PET, PET-PET, CT-CT, 
MRI-PET and other various models.

The Aim of registration was to produce a fusion that when did iso-surface 
render gives me the organ with visible features. So i wrote the algorithm 
with the same intention.

Only stopping criteria that i have used so far is the RMS (mean) value. 
During the calculation of the Deformation field, i have used optical flow 
and geometric information so that I can easily extend this algorithm for 
Range data or to any volume data.

I do sincerely agree that my application still remains undefined, so let's 
assume that my application is to help doctor to get good helth care for 
the paitent. So now if this is my aim, what do you thing are the criteria.

One question though, Can't i write a general purpose 3D elastic 
registration which can deal with volume not necesarily medical volume but 
any volume.

Thanking you, for all the help and care that you have shown to my 
querries.

Regards
Vaijanath


On Fri, 6 Aug 2004, Luis Ibanez wrote:

>
> Hi Vaijanath
>
> Validation of registration is an ill-defined problem.
>
> Even more when dealing with multi-modality and with
> deformable registration.
>
> There is no "right" response for a registration problem.
>
> You will only be able to find a deformation that is
> "good enough" for a particular application given the
> constratints of total computation time and memory
> consumption.
>
> You can always improve a registration at the price
> of consuming more computation time and more memory.
>
> If you don't have a defined applications, you can not
> have a criterion that will tell you what is "good
> enough". In fact, if you don't have an application,
> then you don't have a problem either because there
> is no purpose in registering the images    :-)
>
> Without an application in mind, what you are doing
> is running an optimization method without a stopping
> criterion.
>
> You can, of course, do things like producing fusion
> images with transparency or color encoding for visual
> evaluation. But that will mostly be useful for producing
> nice illustrations for publishing papers, and that only
> helps your CV.
>
> Your registration method "is" correct if it helps a
> Doctor to provide improved health care to a patient.
>
>
> If you are doing registration of PET-CT chances are
> that you are dealing with cancer patients, and that
> your potential medical applications are
>
>  1) Radiation treatment
>  2) Ressection surgery
>  3) Biopsy
>  4) Radiofrequency ablation
>  5) Chemoteraphy evaluation
>
> For each one of them, you will have different requirements
> on the precision with which organs and the tumor should
> be localized, and therefore with what precision you should
> register the two images. The application will also define
> how much computation time it makes sense to invest in the
> registration process.
>
>
>
>   Regards,
>
>
>      Luis
>
>
>
> -----------------------
> V Narasinga Rao wrote:
>
>> Respected Luis,
>> 
>> You have been an great help to me from the time I have joined ITK mailing 
>> list. First of all sorry for a delayed mail, as i was not well for a long 
>> time.
>> 
>> Now abt. the registration algorithm, that I have written. I wanted to get 
>> elastic 3D registration, so I Thought of an algorithm where i will use 
>> curve fitting or deformable registration on the slices and affine transform 
>> as a whole on the volume to get the desired results.
>> 
>> So far i have registered successfully CT - PET modality ( I have little 
>> knowledge of the instruments). I first loaded the all the slices, to 
>> generate the volume. Then sort of normalized teh volumes to have same 
>> origin. After that i registered every slices individually. The slices were 
>> registered with local transformations, while keeping in mind the global 
>> scope. Once i was able to successfully then I did global transformation to 
>> get the entire volume.
>> 
>> So far I am able to register in around 2 mins. two slices CT - PET, of 
>> which CT is 512 X 512 which PET is 128 X 128.
>> 
>> Now as for Validation, Well i am not sure the nature of application, but i 
>> guess i will be doing registration of uni ani multi-modal.
>> 
>> Please let me know weather the method that i have implemented is correct, 
>> Or you would like to see the output and then decide.
>> 
>> I will mail you the results with timming if you require so.
>> 
>> But before finishing off, I would like to thankyou for all the trouble that 
>> you have taken in replying me back, also i owe you a lot for whatever i 
>> have implemented for the registration code.
>> 
>> I joined ITK w/o any knowledge of Imaging, now I can atleast defend the 
>> algorithms that i have written. You have done a lot for me, and i would 
>> like to help you out in anywork that you want.
>> 
>> Once again Thanks for the help that you all people have shown to me.
>> 
>> Regards
>> Vaijanath.
>> 
>> 
>> On Tue, 3 Aug 2004, Luis Ibanez wrote:
>> 
>>> 
>>> 
>>> Hi Narasinga,
>>> 
>>> Please do the following
>>> 
>>> 
>>> 
>>> 1) Read the tutorial on Image Registration
>>> 
>>> http://www.itk.org/CourseWare/Training/RegistrationMethodsOverview.pdf
>>> 
>>> 
>>> 
>>> 2) Read the chapter on Image Registration from the
>>>   ITK Software Guide
>>> 
>>>    http://www.itk.org/ItkSoftwareGuide.pdf
>>> 
>>> 
>>> 
>>> 
>>> The method you describe sounds pretty much like the BSpline
>>> deformable registration illustrated in the example
>>> 
>>> 
>>>       Insight/Examples/Registration/
>>>                 DeformableRegistration4.cxx
>>> 
>>> 
>>> 
>>> 
>>> 3) ITK is N-Dimensional. In ITK you don't do registration
>>>   slice by slice. Instead you use the native dimensionality
>>>   of the datasets.
>>> 
>>> 
>>> 
>>> 
>>> 4) Validation is only possible in the context of
>>> 
>>>    3.1) A clinical application
>>>    3.2) A defined set of image modalities
>>>    3.3) A specific computation time allowable.
>>> 
>>>   Please let us know what your clinical application
>>>   is, what are your image modalities and what are
>>>   the time demands of your clinicians.
>>> 
>>> 
>>> 
>>> 
>>> Regards,
>>> 
>>> 
>>>    Luis
>>> 
>>> 
>>> 
>>> 
>>> -----------------------
>>> V Narasinga Rao wrote:
>>> 
>>>> Hi,
>>>> 
>>>> I have just written an algorithm which registers two images 
>>>> (multi-modality) in Matlab and now i want to shift it to ITK, what is the 
>>>> best way to do it. Also how to validate teh registration algorithm that i 
>>>> ave written. It's absurd question, but since i am not from medical field 
>>>> sp for me it's more important question.
>>>> 
>>>> 
>>>> I would like you all to just have a look at my algo
>>>> for each slice.
>>>> 
>>>> 1. Step 1. Find the region, do it for both images.
>>>> 2. Step 2. Enclose the region with an rectangle, by little geometry the 
>>>> scale and rotation parametr can be found out.
>>>> 3. Step 3. Once you know the scaling and rotation factor apply this to 
>>>> the second image.
>>>> 4. Step 4. Now use curve fitting to fit the curve, thus allignment will 
>>>> happen. 5. Step 5. One you have curve fitted now apply the original 
>>>> images on this binary image and now calculate teh MI to find weather the 
>>>> images are really registrable.
>>>> 
>>>> This entire process can take place for all the sslices in parallel way/
>>>> 
>>>> Currently it is implemented in matlab and has been giving output, 
>>>> ofcourse no validation regarding the registration has been done.
>>>> 
>>>> 
>>>> 
>>>> _______________________________________________
>>>> Insight-users mailing list
>>>> Insight-users at itk.org
>>>> http://www.itk.org/mailman/listinfo/insight-users
>>>> 
>>> 
>>> 
>>> 
>>> 
>>> 
>> 
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