[Insight-users] Peel an image

Wed May 22 20:25:44 EDT 2013

Hi,
I'm not sure I understand completely, but here's my suggestion of an
approach. It may turn out to be easier if you have other staining too.

1) Segment the entire tissue - i.e generate one large object that contains
all your small vessels and a boundary on your layer that you need to peel.
More on how this might be achieved later.

2) Erode this object and use the eroded version to mask out the accidental
staining - i.e. do the peeling. Then apply your normal segmentation to what
is left.

 If you have another channel where all the tissue has contrast then
segmenting the tissue will be relatively easy. Otherwise it will be a bit
more of a challenge. My first guess if the latter is the case is to use 2
markers in a watershed. One marker will be the image border (definitely
outside the tissue). Create the marker image as follows.
   a) Apply a large closing, say about 15% of the tissue size. This will
connect your interior objects together. Threshold the result, choose the
largest connected component, then erode that component a little to make
sure it stays inside the tissue and use the result as your foreground
marker. Use rectangular structuring elements for the closing so you can
take advantage of fast operations.
   b) put the two markers together in an image such that they have
different voxel values - i.e. image border has value 2, inside marker from
step a has value 1.

Use the combined image as the marker image for the morphological markers
filter, use the original as the control. You may need to smooth the
original to close boundary gaps in faint areas. You shouldn't need to take
a gradient because the staining forms a line which the watershed should
find.

Select the foreground label from the watershed result. Erode it a bit
(you'll need to look to confirm how much).

If there is a gap then the watershed will leak through, but this won't
matter as you are going to erode the mask and areas with gaps don't need to
be corrected anyway.

On Thu, May 23, 2013 at 7:47 AM, Gib Bogle <g.bogle at auckland.ac.nz> wrote:

>  I didn't think there would be a stock filter, but maybe somebody else
> has addressed this.
>
> I have attached a typical frame.  I can't show the wanted result, but I
> think it's obvious when you know that the interior of this piece of tissue
> has the blood vessels stained, while the faint rim is clearly not blood
> vessel.  The problem is that there will in general be many vessels stained
> to a similar intensity as this rim.
>
> Gib
>
>
> On 23/05/2013 8:53 a.m., Dženan Zukić wrote:
>
>  I don't think there is any stock filter which does what you want. And I
> still don't understand your situation. Can you show us an example slice and
> wanted result?
>
>
> On Wed, May 22, 2013 at 10:50 PM, Gib Bogle <g.bogle at auckland.ac.nz>wrote:
>
>>  The reason why I don't think erode will work is that the part of the
>> image that contains the information of interest is made up of many
>> disconnected pieces, not very different from the boundary layer that I want
>> to remove.  The only thing that I can use to distinguish the pixels that
>> need to be removed is that they are near the outside of the region.  If I
>> apply erosion I will remove many small but important features (this is
>> labelled vasculature, and I do not want to lose fine capillaries).
>>
>> Gib
>>
>>
>> On 22/05/2013 11:12 p.m., Dženan Zukić wrote:
>>
>>
>> http://www.itk.org/Doxygen/html/group__MathematicalMorphologyImageFilters.html
>>
>>  What you probably want to do is BinaryErode and BinaryDilate.
>>
>>
>> On Wed, May 22, 2013 at 7:04 AM, gib <g.bogle at auckland.ac.nz> wrote:
>>
>>> It's hard to know what to call the processing I want to apply.  I have a
>>> set
>>> of biological images (actually a 3D image, but for now I'm happy to
>>> process
>>> the frames one-by-one) in which the region of interest has an irregular
>>> and
>>> incomplete labelled layer around the boundary.  The staining of the layer
>>> was unintended, and its presence interferes with the segmentation that I
>>> am
>>> doing.  The part of the image that I want to extract is made up of many
>>> disconnected objects, and there is not much difference in the intensity
>>> ranges of the objects of interest and the unwanted edge.  I am willing to
>>> trim a few pixels off the boundary all the way around - this will not
>>> cause
>>> much loss of information.  What I need is way to determine a sequence of
>>> pixels that in some sense defines the extent of the labelled region in
>>> the
>>> image, rather like a 2D shrink wrapping.  I could then use this to shave
>>> or
>>> peel off the outer layer of pixels.
>>>
>>> Does this process have a name?  Are there any existing filters or code
>>> to do
>>> this?  Any clever suggestions (I have some ideas)?
>>>
>>> Thanks
>>> Gib
>>>
>>>
>>>
>>> --
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>>
>>
>>
>>   --
>> Dr. Gib Bogle
>> Senior Research Fellow
>> Auckland Bioengineering Institute
>> University of Auckland
>> New Zealand
>> http://www.bioeng.auckland.ac.nz
>> g.bogle at auckland.ac.nz
>> (64-9) 373-7599 Ext. 87030
>>
>>
>
>
> --
> Dr. Gib Bogle
> Senior Research Fellow
> Auckland Bioengineering Institute
> University of Auckland
> New Zealand
> http://www.bioeng.auckland.ac.nz
> g.bogle at auckland.ac.nz
> (64-9) 373-7599 Ext. 87030
>
>
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>
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