CellProfiler/CellProfiler — Issue #40: JIRA [IMG-1571] tricking IdentifyPrimaryObjects
Author: thouis
Created: 2011-11-23 20:49:39+00:00
State: open
Labels: current

Investigate everything in the following email trail:
At line 719 (in trunk, 705 in release), there's this:"blurred_image =
self.smooth_image(img,mask,1)" located after thresholding but prior to
segmentation.
However, if filter size = 0, smooth_image just returns the original
image; omitting this line makes no difference.
-Mark
On 11/9/2011 1:06 AM, Thouis (Ray) Jones wrote:
> There's a hidden smooth in ID primary. It might be the culprit.
>
> We should expose watershed in one of the image processing modules.
>
> Ray
>
>
> On Tue, Nov 8, 2011 at 23:42, Carolina Wahlby
><carolina@broadinstitute.org> wrote:
>> Hi!
>> A mini-pipeline and the result from CellProfiler attached (running on
>> the image from my previous email). It is the large connected regions I
>> want to chop up based on the local maxima.
>> Many thanks for any input!
>> Cheers
>> Carolina
>>
>>
>> On Tue, Nov 8, 2011 at 5:32 PM, Anne Carpenter<anne@broadinstitute.org> wrote:
>>> Can you send your pipeline, too?
>>>
>>> (and can someone'claim' the project so we don't have six people
>>> working on it once? I know you all want to make Carolina happy but
>>> let's not be redundant)
>>>
>>>
>>>
>>>
>>> On Tue, Nov 8, 2011 at 5:23 PM, Carolina Wahlby
>>><carolina@broadinstitute.org> wrote:
>>>> Hi all,
>>>> I'm preparing a CellProfiler workshop focused on counting signals from
>>>> PLA- and padlock probes in cells and tissue.
>>>> For these images it is often important to separate clusters of signals
>>>> so that a correct count is achieved.
>>>> In theory, watershed segmentation should be able to find as many
>>>> individual objects as there are local intensity peaks. These local
>>>> peaks can also be found using the imextendedmax.m function in Matlab,
>>>> see attached result (desired_regs.pdf) running on attached image
>>>> (blob_details.png). However, I do not manage to get as good separation
>>>> using IdentyfyPrimaryObjects; objects are merged despite turning of
>>>> smoothing etc. Does anyone know a way to trick IdentifyPrimaryObjects
>>>> to get this right? Or is there some other approach? Enhance speckles
>>>> does not do it.
>>>> Thanks
>>>> Carolina
>>>>
>>>> PS
>>>> Matlab code to get desired result:
>>>> I=imread('blob_details.png');
>>>> BW = imextendedmax(I,1);
>>>> figure;subplot(121);imshow(I,[]);hold on; subplot(122);imshow(BW,[]);

Original reporter: leek
Jira link: https://jira.broadinstitute.org/browse/IMG-1571
(Original JIRA has attachments.)
Fix version: Current
Assignee: leek