[ITK-users] Ignore background pixels for gaussian filter computations

[Matt McCormick]

Another approach: mask before passing the data to the filter, too.

Unless the unmasked region is very sparse, skipping the masked region in
general will not speed up the computation -- it may even slow it down,
depending on the implementation. This is due to CPU memory cache pipelines
and the need to treat mask boundaries in a special way.

HTH,
Matt

On Mon, May 1, 2017 at 2:14 PM, Albert Gubern Mérida <
agubernmerida at gmail.com> wrote:

> Thanks Matt! I was not aware of this filter. However, instead of masking
> an image after filtering, I would like that the filter itself ignores a
> specific region (i.e. background) for any calculation. Masking is not
> enough if I apply large sigmas. I am also interested in making the filter
> faster by ignoring computations in specified voxels.
>
> Best,
>
> Albert
>
>
>
> On May 1, 2017 17:22, "Matt McCormick" <matt.mccormick at kitware.com> wrote:
>
>> Hi Albert,
>>
>> The result could be masked. Here's an example of one approach:
>>
>>   https://itk.org/ITKExamples/src/Filtering/LabelMap/MaskOne
>> ImageGivenLabelMap/Documentation.html
>>
>> HTH,
>> Matt
>>
>> On Mon, May 1, 2017 at 8:59 AM, Albert Gubern Mérida <
>> agubernmerida at gmail.com> wrote:
>>
>>> Hi,
>>>
>>> I want to compute voxel features using Gaussian filters such as
>>> LaplacianRecursiveGaussianImageFilter in breast x-ray images. However,
>>> I get very strong responses at the skin line due to the large intensity
>>> difference between tissue and backgound. I do have the segmentation of the
>>> background. Is there anyway to exclude/ignore the background voxels from
>>> the computation using a mask or setting a specific intensity value?
>>>
>>> Thanks!
>>>
>>> Best,
>>>
>>> Albert
>>>
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