Login  Register

Re: Segmentation of objects when the signal intensity varies among them

Posted by Jeremy Adler on Mar 04, 2021; 8:17am
URL: http://imagej.273.s1.nabble.com/Segmentation-of-objects-when-the-signal-intensity-varies-among-them-tp5024496p5024497.html

Hi,

Given that you have identified individual bacteria from the dapi image and assuming that all bacteria are identified;

take each individual dapi ROI, expand it a little (enlarge) and use the enlarged ROI on the FM-64 image. Use one of the automatic thresholding methods.
You are no longer trying to segment the FM-64 image in one go, but piece by piece - knowing that each small area probably contains a single bacteria.

When bacteria form chains - you know their size, so for each chain you can estimate how many bacteria are involved - starting at one end of the chain the look for division at steps matching the size of the bacteria - possibly a slight narrowing of the width.

Jeremy Adler


-----Original Message-----
From: ImageJ Interest Group <[hidden email]> On Behalf Of ekamis
Sent: Thursday, March 4, 2021 8:41 AM
To: [hidden email]
Subject: Segmentation of objects when the signal intensity varies among them

<http://imagej.1557.x6.nabble.com/file/t382821/Example_bacteria_FM4-64.jpg>
<http://imagej.1557.x6.nabble.com/file/t382821/Example_bacteria_FM4-64_BINARY.jpg>
<http://imagej.1557.x6.nabble.com/file/t382821/Example_bacteria_FM4-64_CLEAR.jpg>
Hi,
I am quite new to Fiji and have encountered a following challenge.
I have a set of images of bacteria taken using 2 channels, DAPI (for DNA) and FM-64 (for cellular membrane). My goal is to do the segmentation so that I get a set of individual ROIs (one for each bacterium) based on DNA and another set of individual ROIs based on the membrane. And then I want to measure the features of the objects (bacteria) in the original image surrounded by ROIs.
I constructed a macro that worked OKish for the DAPI channel but not for the
FM4-64 channel. My problem is that I don’t manage to threshold all objects of interest (all bacteria) in one operation. When I try to apply a thresholding algorithm from the available list, some bacteria still remain below the threshold. I assume this is because the FM 4-64 signal is much stronger in some cells then in the others (see picture Example bacteria FM4-64).

I tied to apply Filters (I liked Median the most) and Background Subtraction (radius 10, comparable to the size of my objects) before the thresholding and it helped a bit, but still the pale cells were left as a background.
So what I did was that I ran a 2-step segmantation, the first step for the “bright” cells and the second for the “pale” cells. I am not sure if this an acceptable way to do it. Because I had to apply one thresholding algorithm at the first step, then after the measurements I just cleared the selected ROIs in the original image (which created some “black holes” in it, see picture Example bacteria FM4-64 CLEAR) . And ran another thresholding algorythm (a different one!) on the remaining objects… Another thing I tried was to use a Filter called Unsharp Mask or a CLAHE (Enhance Local Contrast) function, and most cells were identified as objects and thresholded. But since some of the cells form chains, those chains appeared as single particles, so I had to apply Watershed which created some artificial “septa” where they shouldn’t be (see picture Example bacteria
FM4-64 BINARY).
Maybe you could suggest any ideas for a better thresholding? Or pre-processing before the thresholding? Or other options then Watershed to “divide” the cells?




--
Sent from: http://imagej.1557.x6.nabble.com/

--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html








När du har kontakt med oss på Uppsala universitet med e-post så innebär det att vi behandlar dina personuppgifter. För att läsa mer om hur vi gör det kan du läsa här: http://www.uu.se/om-uu/dataskydd-personuppgifter/

E-mailing Uppsala University means that we will process your personal data. For more information on how this is performed, please read here: http://www.uu.se/en/about-uu/data-protection-policy

--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html