How to normalize the nuclear distance channel?

[JimmyCai91]

Hi, great work!

Image data downloaded from those image_data0x.npy files has un-normalized nuclear distance channel. Would be nice if you can provide the way that to normalize the channel to -1 and 1.

Thanks.

[li-li-github]

Hi,

We didn't normalize nuclear distance and I think you shouldn't. Instead, it is rescaled by 0.01.

cytoself/cytoself/datamanager/opencell.py

Line 69 in 0133ab6

intensity_adjustment_default = {'pro': 1, 'nuc': 1, 'nucdist': 0.01}

[JimmyCai91]

Hi,

We didn't normalize nuclear distance and I think you shouldn't. Instead, it is rescaled by 0.01.

cytoself/cytoself/datamanager/opencell.py

Line 69 in 0133ab6

intensity_adjustment_default = {'pro': 1, 'nuc': 1, 'nucdist': 0.01}

Hi @li-li-github

Thanks for your reply. I was using the main branch and didn't notice that there is a pytorch branch. Will take a look. Thanks.

Would you please also help to double check this rescale operation actually aligns with the statement in the paper's method section (https://www.nature.com/articles/s41592-022-01541-z#Sec15) that "The raw pixel intensities in the fluorescence channel are normalized between 0 and 1, and the nuclear distance channel is normalized between −1 and 1."

Thanks,

[Yuangaga]

Hi @li-li-github.

Thanks for your advice. As suggested, I have successfully achieved nuclear segmentation with StarDist.

But, I'm also curious about how to get the nucleus distance matrix from the segmented picture. Could I reference the code for computing nucleus distance? Thanks.

[li-li-github]

Hi @JimmyCai91 and @Yuangaga
I'm very sorry for the late reply.
After checking my old code and recalling my memory, I think what I meant was
making -1 <= the values in the nuclear distance channel =< 1
So it's not "normalized."

This was done by rescaling the channel with 0.01. Throughout the whole dataset that we are offering in this repo, the min value of the nuclear distance channel after rescaling is -1.053 and there are only 118 pixels that are lower than -1, so they should be negligible.
The max value is well below 1.

The idea of making the nuclear distance in [-1, 1] was because, without rescaling, the large values in the nuclear distance channel would overwhelm other channels, resulting in unsuccessful training.

I hope this answered your question.

[JimmyCai91]

Hi @li-li-github ,

Thanks for the reply. It reads great!
I will close this issue.

Thanks,

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@Yuangaga if you need more info, feel free to start a new issue.