Re: Find connected regions 3D / Flood filling 3D from seed region

Posted by Djoere Gaublomme on Oct 07, 2014; 7:12am
URL: http://imagej.273.s1.nabble.com/Find-connected-regions-3D-Flood-filling-3D-from-seed-region-tp5009839p5009928.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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