[Mristudio-users] LDDMM questions

[susumu mori]

Hi Yi,

Landmarker has very strong functionality in landmark-based transformation,
but as you noticed, we haven't made a manual yet. We use landmarks when;

1) Initial linear transformation failed with some reasons (brain locations,
orientations, and FOV coverages are too different).
2) Two images have so much different contrasts (e.g. normalizing 0 year to 1
year old neonates)
3) When the patient has strong anatomical deformation such as tumor and
chronic stroke and want to ignore some regions of the brain.

We'll do our best to make a PPT "getting started" shortly.

Susumu


On Wed, Jul 15, 2009 at 2:30 PM, Yi Jiang <yj3 at duke.edu> wrote:

>  Hello, Dr Mori,
>
>
>
> Thank you very much for your reply. It's very clear. Also, I really
> appreciate all the help from Xin and Anthony. They are really quick and
> helpful, and they have solved all my problems so far.
>
>
>
> I have one more question:
>
>
>
> It seems there is no manual or instruction about using LDDMM with manually
> placed landmarkers. Is there such a function? Or is the current LDDMM only
> working without landmarker? If yes, how do we do that? Just add some
> landmarkers and then start a LDDMM job?
>
>
>
> Thank you!
>
>
>
> Best,
>
> Yi
>
>
>
>
> ----- Original Message -----
>
> *From:* susumu mori <susumu at mri.jhu.edu>
> *To:* Yi Jiang <yj3 at duke.edu> ; DTI Studio, ROI Editor, Landmarker
> Questions/Support <mristudio-users at mristudio.org> ; Xin Li<xli16 at jhmi.edu>
> *Sent:* Tuesday, July 14, 2009 2:21 AM
> *Subject:* Re: [Mristudio-users] LDDMM questions
>
> Hi Yi,
>
> 1) I recommend you to do AIR first from two reasons. First one is a
> practical reason. Our LDDMM requires that the matrix and pixel sizes of the
> two images are identical. After AIR, even if the input images have different
> dimensions, the output will have the same dimension. This is handy. Second
> one is more important. Let me use fitting of a X-Y plot for analogy. When
> you use linear fitting, no matter which software you use, the results are
> almost identical. This is because the energy landscape of linear fitting
> usually has a very simple "one-valley" shape, meaning the results always
> converge at the same solution. On the other hand, when you are using
> non-linear fitting, you are required to provide initial values, which are
> close to the real solution. Usually you first do linear solution and then
> use the result as the initial value for the subsequent non-linear fitting.
> This is because the energy landscape of non-linear fitting has a complicated
> "multi-valley" shape. If your initial values are far away from the real
> solution, the fitting is trapped by a local minima.
>
> Non-linear warping is very similar. You are required to bring two brains as
> close as possible before you start non-linear warping.
>
> When you adopt AIR+LDDMM, you have to transform the image twice, including
> tensor reorientation. Landmarker can combine transformation matrices so that
> you can do multiple transformation at once to avoid multiple interpolation.
>
> Xin, can we combine AIR matrix and LDDMM matrix?
>
> 2) We usually don't use non-linear AIR. So we don't have much experience
> with it. Yes, it should do tensor reorientation if you apply the
> transformation to a tensor file.
>
>
>
> On Mon, Jul 13, 2009 at 4:12 PM, Yi Jiang <yj3 at duke.edu> wrote:
>
>>  Dear All,
>>
>> I have two questions about LDDMM:
>>
>>
>>
>> 1. if I have a template image and a subject image and I want to register
>> these two by LDDMM eventually, 1). should I use LDDMM to register these two
>> directly or 2). should I use AIR linear to affine transform them first, and
>> then LDDMM the updated subject image? In the 2nd case, I need to reorient
>> tensors twice, once by the AIR transformation matrix and once by the LDDMM
>> transformation matrix, right?
>>
>>
>>
>> I am asking this question because for some other registration software I
>> have used, it seems the elastic transformation works better after affine
>> registering the images first.
>>
>>
>>
>> Or maybe LDDMM covers rigid and affine transformation well already so we
>> can do #1?
>>
>>
>>
>> 2. How does the nonlinear AIR compensate/compare with LDDMM? Can the
>> nonlinear AIR transformation be applied to reorient tensors?
>>
>>
>>
>> Thank you very much!
>>
>>
>>
>> Best,
>>
>> Yi
>>
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