[ITK-users] [ITK] Normalized Cross Correlation returns perfect alignment with images not even overlapping

[Andrew Harris]

Hello Francois and Dženan,

Because of the way the images were captured, there is a known common point
of overlap, so we set the centre to that point in the expectation that the
transform would rotate and translate about that point when the registration
is run.  Have I misunderstood the design or is that what should be
happening?

--

AH


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On Tue, Apr 11, 2017 at 9:00 AM, Francois Budin <francois.budin at kitware.com>
wrote:

> Hello Andrew,
>
> Did you try to initialize the registration with [1] for example?
> If the images do not overlap at all at the beginning of the registration,
> the algorithm might only do what Dżenan said, match black pixels.
> Initializing the transform should help.
>
> Hope this helps,
> Francois
>
> [1] https://itk.org/Doxygen/html/classitk_1_1CenteredTransformInitializer.
> html
>
> On Tue, Apr 11, 2017 at 8:36 AM, Andrew Harris <aharr8 at uwo.ca> wrote:
>
>> In the image mask, the parts we want to include in the calculation are
>> bright and the parts that we want to exclude are dark, is that the opposite
>> of what it should be?
>>
>> --
>>
>> AH
>>
>>
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>> On Thu, Mar 30, 2017 at 7:25 PM, Dženan Zukić <dzenanz at gmail.com> wrote:
>>
>>> Hi Andrew,
>>>
>>> your masks might be inverted. If NCC gets all black pixels in both
>>> images, the correlation will be perfect.
>>>
>>> Regards,
>>> Dženan
>>>
>>> On Thu, Mar 30, 2017 at 2:13 PM, Andrew Harris <aharr8 at uwo.ca> wrote:
>>>
>>>> Hi, I'm hoping someone can guide me toward an explanation of this.  I
>>>> run my pipeline on various ultrasound image sets and get an NCC between
>>>> 0.65 and 0.8 for good alignments, but on some sets the NCC returns 1.0 when
>>>> the images aren't even overlapping.  I have the black areas of the image
>>>> masked out, and have even tried cranking up the threshold to be sure the
>>>> darker areas aren't being included to no avail.  Any thoughts?
>>>>
>>>> --
>>>>
>>>> AH
>>>>
>>>>
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