Autophagy Analysis using ImageJ

classic Classic list List threaded Threaded
5 messages Options
Reply | Threaded
Open this post in threaded view
|

Autophagy Analysis using ImageJ

Rohitesh Gupta
Hi All,

I am writing after a long long time.
I have an image which has white dots inside the cells and I wanted to compare this image with another image which doesn't have white dots inside the cells. The objective is to count no. of cells with white dots (vacuoles) and not those cells where the vacuoles are absent. Please suggest which approach can be used on imagej.

Thanks,
Rohitesh

--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html
Reply | Threaded
Open this post in threaded view
|

Re: Autophagy Analysis using ImageJ

Krs5
Dear Rohitesh,

This depends a little on your images and your cells. For example: Can you identify individual cells? Is there one vacuole/cell? Do you have a nuclear staining?

Maybe you can show a few images?

Best wishes

Kees


Dr Ir K.R. Straatman
Senior Experimental Officer
Advanced Imaging Facility
Centre for Core Biotechnology Services
University of Leicester
www.le.ac.uk/advanced-imaging-facility


-----Original Message-----
From: Rohitesh Gupta <[hidden email]>
Sent: 09 October 2019 14:26
Subject: Autophagy Analysis using ImageJ

Hi All,

I am writing after a long long time.
I have an image which has white dots inside the cells and I wanted to compare this image with another image which doesn't have white dots inside the cells. The objective is to count no. of cells with white dots (vacuoles) and not those cells where the vacuoles are absent. Please suggest which approach can be used on imagej.

Thanks,
Rohitesh

--
ImageJ mailing list: https://eur03.safelinks.protection.outlook.com/?url=http%3A%2F%2Fimagej.nih.gov%2Fij%2Flist.html&amp;data=02%7C01%7Ckrs5%40leicester.ac.uk%7C4023d42fbfec4c5ccc3608d74cbc6a34%7Caebecd6a31d44b0195ce8274afe853d9%7C0%7C1%7C637062244440134706&amp;sdata=ZK3ftGcIwoWQgMWyViX8x2ZVr3YPfJ3lRGuo%2BYfZvXQ%3D&amp;reserved=0

--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html
Reply | Threaded
Open this post in threaded view
|

Re: Autophagy Analysis using ImageJ

Rohitesh Gupta
In reply to this post by Rohitesh Gupta
Dear Kees,

I was able to split the channel and identify that the vacuoles fall under the green channel. Every cell has one vacuole and each cell is distinctly identified. I am sharing here an image for reference. Please share if there is any alternate strategy for the same.

Thanks,
Rohitesh

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

laxmi.png (269K) Download Attachment
Reply | Threaded
Open this post in threaded view
|

Re: Autophagy Analysis using ImageJ

Krs5
Dear Rohitesh

One option would be:
After splitting your channels you can threshold your red channel to identify the individual cells
- Optimize brightness/contrast (Image > Adjust > Brightness/Contrast and Apply
- Image > Adjust >Threshold and select a threshold that works
- Process > Binary > Watershed and you more or less should have individual cells. If there are too many clumps of cells try a different threshold setting

Add these cells to the ROI Manager
- Analyze > Analyze Particles; Set a pixel size that excludes small particles, Select 'Add to Manager' and 'Exclude on edges'

You could now select Analyze > Set Measurements and select 'Min & max gray value'

Select your image with the vacuoles and In the ROI Manager under More>> select 'Multi Measure' and deselect all in the next menu. You should now get a list of all cells with their minimum and maximum grey scale value. The maximum grey scale value can be used to identify ROIs (cells) with a vacuole, in you example all above 60.

Hope it works

Best wishes

Kees

-----Original Message-----
From: ImageJ Interest Group <[hidden email]> On Behalf Of Rohitesh Gupta
Sent: 09 October 2019 14:53
To: [hidden email]
Subject: Re: Autophagy Analysis using ImageJ

Dear Kees,

I was able to split the channel and identify that the vacuoles fall under the green channel. Every cell has one vacuole and each cell is distinctly identified. I am sharing here an image for reference. Please share if there is any alternate strategy for the same.

Thanks,
Rohitesh

--
ImageJ mailing list: https://eur03.safelinks.protection.outlook.com/?url=http%3A%2F%2Fimagej.nih.gov%2Fij%2Flist.html&amp;data=02%7C01%7Ckrs5%40leicester.ac.uk%7C5c4a116adf13420409b608d74cc02724%7Caebecd6a31d44b0195ce8274afe853d9%7C0%7C1%7C637062260495574847&amp;sdata=D0Ki02Qs37feqZjGA2ws6Z%2Fz5cszi7LFVAi%2BubMIChs%3D&amp;reserved=0

--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html
Reply | Threaded
Open this post in threaded view
|

Re: Autophagy Analysis using ImageJ

Herbie
In reply to this post by Rohitesh Gupta
Good day Rohitesh,

although a separation and count of the two types of cells appears
possible for the provided sample image (I use the magenta channel after
color transformation to CMYK) I should like to tell you that the sample
image is of poor quality:

1.
Less than half of the 8bit dynamic range is used

2.
The image appears out-of-focus

3.
The cells show a strange halo that is not caused by de-focusing

Please check the setup of your microscope, the camera exposure, and
provide unprocessed (raw) images.

Regards

Herbie

::::::::::::::::::::::::::::::::::::::::::::
Am 09.10.19 um 15:53 schrieb Rohitesh Gupta:

> Dear Kees,
>
> I was able to split the channel and identify that the vacuoles fall under the green channel. Every cell has one vacuole and each cell is distinctly identified. I am sharing here an image for reference. Please share if there is any alternate strategy for the same.
>
> Thanks,
> Rohitesh
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html
>

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