No subject

verflow or windowing occuring? Maybe check the output pixel types and outpu=
t histograms.

HTH,
Matt

PS.  Please reply-to-all so the message reaches the mailing list.

On Mon, Aug 5, 2013 at 7:57 AM, Lopez Saratxaga, Cristina <Cristina.Lopez at t=
ecnalia.com> wrote:
> Hello Matt,
>
> Thanks a lot for your suggestion!!!
>
> I've tried it (sorry, not before because I've been out of the office some=
 days) and the liver registration has improve a lot! However, the images lo=
ok quite strange after the registration.  It looks as if the pixels of the =
two input images were mixed, but with very different intensity values. Plea=
se, open attached to see what I mean.
>
> Why could this be happening? How could I avoid this situation? The defaul=
t pixel value is currently set to gray...
>
> Thanks a lot in advance.
>
> Kind regards,
>
> Cristina
>
> -----Mensaje original-----
> De: Matt McCormick [mailto:matt.mccormick at kitware.com]
> Enviado el: lunes, 29 de julio de 2013 16:44
> Para: Lopez Saratxaga, Cristina
> CC: insight-users at itk.org
> Asunto: Re: [Insight-users] Liver registration in MRI slices
>
> Hi Cristina,
>
> It is possible to just specify the liver for the registration with SetFix=
edImageRegion [1].
>
> Hope this helps,
> Matt
>
> [1] =20
> http://www.itk.org/Doxygen/html/classitk_1_1ImageRegistrationMethod.ht
> ml#abfd3451ef972f883682ef7b530cdbdb4
>
> On Mon, Jul 29, 2013 at 9:05 AM, Lopez Saratxaga, Cristina <Cristina.Lope=
z at tecnalia.com> wrote:
>> Dear all,
>>
>>
>>
>> I've several sets of MRI images, each one with different sequences=20
>> and multiple slices within each.  You can see attached an example of=20
>> a slice (axial view).
>>
>>
>>
>> Our goal is to produce an automatic segmentation of the liver=20
>> (located at the left side) taking into consideration the information=20
>> not only of the different slices of one sequence, but the information=20
>> contained in various sequences in order to create a 3D model of the=20
>> liver. One colleague is already working on in, but in order to make=20
>> sure that the segmentation is done as best as possible, we need to=20
>> perform a registration of the slices through the various sequences.
>>
>>
>>
>> At first I tried with basic transformation as the Affine of=20
>> Deformable, applying diverse metric and optimizer, but the=20
>> segmentation didn't improve in any respect. These transformations=20
>> work fine, but the problem is that the registration is mainly made in=20
>> the contours of the image (2D registration performed better than 3D=20
>> registration). What I would like, would be to just focus in the=20
>> region of the slice where the liver should be located and focus the=20
>> registration on the liver, however, I'm afraid that I don't know how to =
perform this.
>>
>>
>>
>> I've read something about registrations based of features. The=20
>> landmark based registration sounds interesting but it seems that it's=20
>> necessary to define a set of reference points both if the fixed and=20
>> the moving image, something that I don't have. At the most, I could=20
>> have some approximate reference points for the fixed image, but not for =
the moving one.
>> Additionally, I've also read something about masks and ROIs. I tried=20
>> the example ImageRegistration12 with a binary mask, however, the=20
>> results were not as expected (maybe I was not using well the mask).
>>
>>
>>
>> At this time, I'm a bit lot with this problem and I really don't know=20
>> how to proceed with the registration problem, so any idea on how to=20
>> deal with this problem will be really appreciated!
>>
>> Many thanks in advance for your Help!!
>>
>>
>>
>> Kind regards,
>>
>>
>>
>> Cristina
>>
>>
>>
>>
>> _____________________________________
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>>
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Please keep messages on-topic and check the ITK FAQ at:
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