http://imagej.273.s1.nabble.com/Find-connected-regions-3D-Flood-filling-3D-from-seed-region-tp5009839p5009929.html
> Hello,
>
> Unfortunately these solutions don't seem to solve the problem at hand.
>
> If I understand correctly, the "Connected Component Labeling" from the
> IJPB plugin only works on binary images, whereas I want to perform the
> connecting on a grayscale image, based on a seed region that is binary.
>
> The spot detection plugin comes very close to what is desired, but the
> criteria for object extension are not the correct ones in this case.
> For example, if I understand correctly, "Constant" would extend the seed
> whenever a neighbouring voxel of my seed region is above the "Constant"
> gray value, regardless of what the gray value of the seed voxel next to
> it is.
>
> What I am looking for is an extension of my seed regions that acts like
> a 3D flood fill, namely that all connected voxels with the same
> grayscale value will be selected.
>
> Does anybody know if this exists?
>
> Thanks in advance
>
> Djoere
>
>
>
> Quoting Djoere Gaublomme <
[hidden email]>:
>
>> Thanks for the replies Ignacio and Thomas, I will check these out!
>>
>> Kind regards
>>
>> Djoere
>>
>>
>> Quoting Thomas Boudier <
[hidden email]>:
>>
>>> Hi Djoere,
>>>
>>> Not sure to fully understand, but it seems that you have some seeds,
>>> and want to aggregate voxels to these seeds based on some criteria.
>>> May be have a look to some spots detection plugins like
>>>
>>>
http://imagejdocu.tudor.lu/doku.php?id=plugin:segmentation:3d_spots_segmentation:start&s[]=spots&s[]=detection
>>>
>>>
>>> you need two images, one with seeds (may be you need to "draw" your
>>> rois) and a signal image, it uses local threshold to aggregate voxels
>>> to the seeds, in your case, local threshold is a constant.
>>>
>>> Hope this helps
>>>
>>> Thomas
>>>
>>
>>
>>
>> Quoting Ignacio Arganda-Carreras <
[hidden email]>:
>>
>>> Hello Djoere,
>>>
>>> You might want to install the IJPB-plugins library. It comes with an
>>> efficient implementation of Connected Components in 3D that you can
>>> use to
>>> find the region you want after binarizing it with the proper threshold.
>>>
>>>
http://github.com/ijpb/ijpb-plugins>>>
>>> After installation, you should have the plugin under "Plugins > Fast
>>> Morphology > Binary Images > Connected Component Labeling".
>>>
>>> Let me know if you need more help,
>>>
>>> ignacio
>>
>>
>>
>>
>>> On 01/10/14 16:54, Djoere Gaublomme wrote:
>>>> Hi,
>>>>
>>>> I want to perform an action on a large 3D image stack (8-bit grayscale,
>>>> approximately 800x800x800 and 500 MB).
>>>> The action I want to do is to start from a selected ROI (preferably
>>>> based on a separate Mask image) and find all neighbouring voxels with
>>>> the same gray values (for clarification: I only want to select voxels
>>>> that have the same gray value as a selected neighbouring voxel). It
>>>> does not matter whether gray value information is retained in the
>>>> resulting image or not.
>>>>
>>>> For now, the only solution I found was to add an object to the 3D
>>>> Manager from the Mask image, then put this selection on the grayscale
>>>> stack and run "Find Connected Regions"
>>>> [
http://www.longair.net/edinburgh/imagej/find-connected-regions/ , with
>>>> the following parameters : run("Find Connected Regions", "
>>>> display_one_image display_results regions_must
>>>> regions_for_values_over=1
>>>> minimum_number_of_points=1 stop_after=-1"); ]
>>>>
>>>> However, this takes forever to process, so I am wondering if there is a
>>>> faster alternative (and preferably one that is macro-friendly).
>>>> I have tried Flood Fill (3D), but this does not appear to work with a
>>>> seed region.
>>>>
>>>> Thanks in advance!
>>>>
>>>> Djoere
>>>>
>>>> --
>>>> ImageJ mailing list:
http://imagej.nih.gov/ij/list.html>>>>
>>>
>>> --
>>> /***************************************************************/
>>> Thomas Boudier, Associate Professor, UPMC,
>>> Université Pierre et Marie Curie, Paris, France.
>>> BioInformatics Institute (BII)/IPAL, Singapore.
>>> /**************************************************************/
>>>
>>> --
>>> ImageJ mailing list:
http://imagej.nih.gov/ij/list.html>>
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>> ImageJ mailing list:
http://imagej.nih.gov/ij/list.html>
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