soma area detection
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Hi,
As a new user of ImageJ. I am trying to automate some of my measurements about neuronal sizes. Has anyone tried before or know how to identify cell soma apart from their processes? The regular threshold tool or edge detector would fail because of the presence of the process or the nuclei. Thanks a lot for your time. Qing |
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Here's a quick idea. I don't know how well it will work, but I'm thinking that the Watershed program might cut off the the processes. Then you could iterate through the ROI's created to see which one is most circular (soma). If you give me a picture, I'll come up with something. |
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In reply to this post by Qing Liu
Here's a quick idea. I don't know how well it will work, but I'm thinking that the Watershed program might cut off the the processes. Then you could iterate through the ROI's created to see which one is most circular (soma). If you give me a picture, I'll come up with something. |
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In reply to this post by Qing Liu
Dear all, I have found a solution to select neuronal soma but need your
suggestions to do so in imageJ. http://dl.dropbox.com/u/266880/Soma.pdf In the above paper, they mentioned the images of the neurons stained > for beta-III tubulin are first Gaussian filtered to suppress image > noise. They are background corrected using a top hat morphological filter > with a disk structuring element larger than the > size of the largest cell body. A morphological opening > with a structuring element of a diameter smaller than the cell > body but larger than all neurites permits suppressing neuritelike > structures. > I am a little confused about the second and third step and wonder if anyone can help. Thank you. Qing |
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Hi Quing,
here is an attempt to translate the recipe into ImageJ commands: Top-hat with circular kernel of radius r: - duplicate the image Assuming that your foreground objects have higher pixel value than the background: - Process>Filters>Minimum on the copy, radius r, followed by - Process>Filters>Maximum on the copy, same radius r - Image calculator to subtract the copy from the original If your foreground pixel values are smaller than those of the background, exchange Min&Max, and subtract the original from the copy. Morphological opening: - Process>Filters>Minimum with radius r1 (smaller than r for the top- hat), then - Process>Filters>Maximum with the same radius r1 Michael ________________________________________________________________ On 19 Apr 2011, at 00:39, Qing Liu wrote: > Dear all, I have found a solution to select neuronal soma but need > your > suggestions to do so in imageJ. > > http://dl.dropbox.com/u/266880/Soma.pdf > > In the above paper, they mentioned > > the images of the neurons stained >> for beta-III tubulin are first Gaussian filtered to suppress image >> noise. They are background corrected using a top hat morphological >> filter >> with a disk structuring element larger than the >> size of the largest cell body. A morphological opening >> with a structuring element of a diameter smaller than the cell >> body but larger than all neurites permits suppressing neuritelike >> structures. >> > > I am a little confused about the second and third step and wonder > if anyone > can help. > > Thank you. > > Qing |
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Hi, Michael,
Thank you for your suggestion. I am able to achieve better results with Matlab morphological opening functions (strel and imopen): http://www.mathworks.com/help/toolbox/images/ref/imopen.html. With brightness/contrast/level adjustment in ImageJ and the morphological opening settings in Matlab, I could suppress the neurites but the nuclei seem to be problematic for applying threshold segmentation tool to measure the soma size. Any suggestions for filling the holes/nuclei in the grayscale image before the reconstruction? Thanks in advance. Before: http://dl.dropbox.com/u/266880/start.tif After: http://dl.dropbox.com/u/266880/MorphologicalOpening.tif Qing On Tue, Apr 19, 2011 at 4:39 AM, Michael Schmid <[hidden email]>wrote: > Hi Quing, > > here is an attempt to translate the recipe into ImageJ commands: > > Top-hat with circular kernel of radius r: > - duplicate the image > Assuming that your foreground objects have higher pixel value > than the background: > - Process>Filters>Minimum on the copy, radius r, followed by > - Process>Filters>Maximum on the copy, same radius r > - Image calculator to subtract the copy from the original > If your foreground pixel values are smaller than those of the background, > exchange Min&Max, and subtract the original from the copy. > > Morphological opening: > - Process>Filters>Minimum with radius r1 (smaller than r for the top-hat), > then > - Process>Filters>Maximum with the same radius r1 > > > Michael > ________________________________________________________________ > > > On 19 Apr 2011, at 00:39, Qing Liu wrote: > > Dear all, I have found a solution to select neuronal soma but need your >> suggestions to do so in imageJ. >> >> http://dl.dropbox.com/u/266880/Soma.pdf >> >> In the above paper, they mentioned >> >> the images of the neurons stained >> >>> for beta-III tubulin are first Gaussian filtered to suppress image >>> noise. They are background corrected using a top hat morphological filter >>> with a disk structuring element larger than the >>> size of the largest cell body. A morphological opening >>> with a structuring element of a diameter smaller than the cell >>> body but larger than all neurites permits suppressing neuritelike >>> structures. >>> >>> >> I am a little confused about the second and third step and wonder if >> anyone >> can help. >> >> Thank you. >> >> Qing >> > |
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Hi Quing,
As I am not a biologist I don't know what structures you want to extract from your image - I hope for the biologists on the list to solve that problem. Concerning ImageJ vs. Matlab: As far as I can say from the sample image on the MatLab site, the operation is exactly the same as minimum+maximum in ImageJ, but there is a slight difference of kernel size: Matlab says the radius is 5; I have to use a radius of 4.5 in ImageJ for the same result. This is not astonishing - there are different conventions for the radius. Otherwise, only the brightness&contrast of the output image has been readjusted to fit the 0-255 range of 8-bit data, then you get the same as on the Matlab site. Michael ________________________________________________________________ On 19 Apr 2011, at 23:53, Qing Liu wrote: > Hi, Michael, > > Thank you for your suggestion. I am able to achieve better results > with > Matlab morphological opening functions (strel and imopen): > http://www.mathworks.com/help/toolbox/images/ref/imopen.html. > > With brightness/contrast/level adjustment in ImageJ and the > morphological > opening settings in Matlab, I could suppress the neurites but the > nuclei > seem to be problematic for applying threshold segmentation tool to > measure > the soma size. Any suggestions for filling the holes/nuclei in the > grayscale > image before the reconstruction? Thanks in advance. > > Before: http://dl.dropbox.com/u/266880/start.tif > After: http://dl.dropbox.com/u/266880/MorphologicalOpening.tif > > Qing > > > On Tue, Apr 19, 2011 at 4:39 AM, Michael Schmid > <[hidden email]>wrote: > >> Hi Quing, >> >> here is an attempt to translate the recipe into ImageJ commands: >> >> Top-hat with circular kernel of radius r: >> - duplicate the image >> Assuming that your foreground objects have higher pixel value >> than the background: >> - Process>Filters>Minimum on the copy, radius r, followed by >> - Process>Filters>Maximum on the copy, same radius r >> - Image calculator to subtract the copy from the original >> If your foreground pixel values are smaller than those of the >> background, >> exchange Min&Max, and subtract the original from the copy. >> >> Morphological opening: >> - Process>Filters>Minimum with radius r1 (smaller than r for the >> top-hat), >> then >> - Process>Filters>Maximum with the same radius r1 >> >> >> Michael >> ________________________________________________________________ >> >> >> On 19 Apr 2011, at 00:39, Qing Liu wrote: >> >> Dear all, I have found a solution to select neuronal soma but >> need your >>> suggestions to do so in imageJ. >>> >>> http://dl.dropbox.com/u/266880/Soma.pdf >>> >>> In the above paper, they mentioned >>> >>> the images of the neurons stained >>> >>>> for beta-III tubulin are first Gaussian filtered to suppress image >>>> noise. They are background corrected using a top hat >>>> morphological filter >>>> with a disk structuring element larger than the >>>> size of the largest cell body. A morphological opening >>>> with a structuring element of a diameter smaller than the cell >>>> body but larger than all neurites permits suppressing neuritelike >>>> structures. >>>> >>>> >>> I am a little confused about the second and third step and wonder if >>> anyone >>> can help. >>> >>> Thank you. >>> >>> Qing >>> >> |
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