Greetings Anu,
because you called my suggestion as being your "last option" I should
like to remark that this idea is exactly *contrary* to what I've suggested.
My prognosis is, that you will invest a lot of time with learning and
trying various (advanced) approaches and then realize that none of them
works fully automatically, i.e. will need additional manual
interventions that again take time. In the end you may realize that the
better (quicker) approach would have been to start immediately with the
manual segmentation of your 50 images.
Last but not least, if things would be so easy and economic with using
(advanced) approaches, why then don't we see any results that are fully
automatically obtained from your sample image?
Good luck
Herbie
::::::::::::::::::::::::::::::::::::::::
Am 08.03.24 um 19:01 schrieb anusuya pal:
Thanks so much everyone for suggesting so many ways. Thanks, Herbie, yes,
that's the last option I thought. :-)
I really like Ankit's proposal as it's very much automated. The idea given
by Michael -- I am kind of doing that for finding the spacing between the
consecutive petal like patterns. But, that doesn't give me a good estimate
for all of my images, as it is just one type of pattern.
I also like Curtis's idea, I need to play with that as suggested for the
various patterns to see which one works the best.
I really appreciate your valuable time and suggestions.
Thanks,
Anu
On Saturday, March 9, 2024, Curtis Rueden <[email protected]> wrote:
Hi Anu,
I think your segmentation can be automated, but it is a bit tricky. Here is
a quick attempt I made:
1. Labkit - https://imagej.net/plugins/labkit/
This is a machine-learning based pixel classification, where you do manual
painting over the different areas of your image. Then train it, and paint
again over the parts it got wrong. Repeat until it learns well how things
should be.
Here is how it looked for me after I did this process back and forth a
couple of times:
[image: labkit-small.png]
As you can see, it is not perfect, but it gets close enough that you can
then do additional steps afterward to extract the information you want.
Then, you can save the classifier and apply it to as many other similar
images as you want.
Note that Labkit (at least in my hands today) has an annoying bug where
after running the classifier (Ctrl+Shift+T), the pencil tool sometimes
stops being able to paint lines until you click (or Alt+Tab) away from the
Labkit window and then back.
2. Export probability map to ImageJ
This gets you back to a regular image window, which you can then manipulate
with other plugins.
You might always want to save this image to a TIFF file now, since it will
serve as a good starting point for further experimentation.
3. Smooth the image to reduce noise. I used the Kuwahara filter. But it
didn't want to run on a 32-bit multichannel image, so I had to first run
Image > Type > 8-bit and then Duplicate only the first slice of the image.
The easiest way to run it is to type "kuwa" into the search bar of Fiji.
After running this filter with a smoothing window of 5, my image looked
like this:
[image: smoothed-small.png]
4. Do the actual segmentation with the Morphological Segmentation plugin,
part of MorphoLibJ. https://imagej.net/plugins/morpholibj
For this plugin you will need to enable the IJPB-plugins update site via
Help > Update..., "Manage Update Sites" button, in Fiji.
I left the input image as Border Image, changed Tolerance to 30, clicked
Run, and then changed the Results Display to "Catchment basins". Here is
what that looked like:
[image: morpholibj-small.png]
As you can see, it erroneously bisected two of the regions on the bottom
half, as well as one on the top half, but it got most of then right.
5. You could then click "Create image" to make another image and measure
the number of pixels of each color to get the size of each region. And
filter out results that aren't close to the expected size, or aren't at the
correct (X,Y) coordinates to be one of the petal shapes.
I would also suggest to give CellPose a try—I did not try it, but it does
very well on a wide variety of input images.
You might get better answers on https://forum.image.sc rather than here,
since the state-of-the-art for segmenting scientific images has changed a
lot in recent years and there are many more powerful tools than classical
ImageJ-based segmentation now.
Regards,
Curtis
--
Curtis Rueden
Software architect, LOCI/Eliceiri lab - https://uw-loci.github.io/
ImageJ2 lead, Fiji maintainer - https://imagej.net/people/ctrueden
Have you tried the Image.sc Forum? https://forum.image.sc/
On Fri, Mar 8, 2024 at 1:48 AM anusuya pal <[email protected]> wrote:
Dear all,
I want to measure the area of the flower-like patterns as shown in the
image. I can do it manually, but I have more than 50 images. Do you have
any suggestions for doing it automatically?
Thanks for your help,
Anu
--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html
--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html
--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html
--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html
