Usage of mask flage in ts_aretomo
22 views
Skip to first unread message
Deli
Apr 30, 2026, 9:43:13 AMApr 30
to war...@googlegroups.com
Hi everyone,
I would like to use ts_aretomo/ --mask flag on warp.
I don't understand what precisely it does to be able to troubleshoot. I would appreciate any information.
Thank you,
Delnia
Delnia NAZARI, PhD student
Team "Cellular Architecture" (Dr. Florian Faessler)
Department of Integrated Structural Biology
IGBMC | Institute of Genetic and of Molecular and Cellular Biology
1, rue Laurent Fries 67404 Illkirch
---------------------------------------------------------------------------------------
Office: IGBMC RDC, 0011
Phone: (+33 3 88 65 00 11)
Warp Bot
Apr 30, 2026, 12:48:57 PMApr 30
to war...@googlegroups.com, Deli
Hi Delnia,
The --mask flag in ts_aretomo tells WarpTools to apply per-tilt masks when building the image stacks that get passed to AreTomo2 for alignment.
These masks come from the BoxNet neural network step during frame series processing. If you ran BoxNet on your frame series (the "pick particle" / masking option), it creates a binary mask for each micrograph that marks "dirt" regions -- things like ice contamination, carbon edges, gold bead residue, or other artifacts.
When you enable --mask in ts_aretomo, for each tilt image:
1. The corresponding BoxNet mask is loaded and rescaled to the stack's pixel size.
2. Connected components in the mask are identified (i.e. individual dirt patches).
3. For each patch, the mean and standard deviation of the surrounding (non-masked) pixel intensities are calculated.
4. The masked pixels are replaced with Gaussian random noise matching those local statistics, with a soft edge to blend smoothly into the surrounding image.
The result is that artifacts are replaced with featureless noise that won't confuse AreTomo's alignment procedure. This can improve tilt series alignment quality when your images contain contamination or other high-contrast features that would otherwise dominate the cross-correlation.
For this flag to work, you need to have BoxNet masking results from the frame series processing step. If no mask files exist for a given tilt, that tilt is simply left unmodified.
— Warp Bot
THIS IS AN AUTOMATED MESSAGE GENERATED BY AN LLM. IT MAY OR MAY NOT SOLVE YOUR PROBLEM. IF YOU'D LIKE TO SPEAK TO A HUMAN, SAY SO IN YOUR MESSAGE.
The --mask flag in ts_aretomo tells WarpTools to apply per-tilt masks when building the image stacks that get passed to AreTomo2 for alignment.
These masks come from the BoxNet neural network step during frame series processing. If you ran BoxNet on your frame series (the "pick particle" / masking option), it creates a binary mask for each micrograph that marks "dirt" regions -- things like ice contamination, carbon edges, gold bead residue, or other artifacts.
When you enable --mask in ts_aretomo, for each tilt image:
1. The corresponding BoxNet mask is loaded and rescaled to the stack's pixel size.
2. Connected components in the mask are identified (i.e. individual dirt patches).
3. For each patch, the mean and standard deviation of the surrounding (non-masked) pixel intensities are calculated.
4. The masked pixels are replaced with Gaussian random noise matching those local statistics, with a soft edge to blend smoothly into the surrounding image.
The result is that artifacts are replaced with featureless noise that won't confuse AreTomo's alignment procedure. This can improve tilt series alignment quality when your images contain contamination or other high-contrast features that would otherwise dominate the cross-correlation.
For this flag to work, you need to have BoxNet masking results from the frame series processing step. If no mask files exist for a given tilt, that tilt is simply left unmodified.
— Warp Bot
THIS IS AN AUTOMATED MESSAGE GENERATED BY AN LLM. IT MAY OR MAY NOT SOLVE YOUR PROBLEM. IF YOU'D LIKE TO SPEAK TO A HUMAN, SAY SO IN YOUR MESSAGE.
--
You received this message because you are subscribed to the Google Groups "Warp" group.
To unsubscribe from this group and stop receiving emails from it, send an email to warp-em+u...@googlegroups.com.
To view this discussion visit https://groups.google.com/d/msgid/warp-em/CANZwa8tvaQx%3DyQprtqBhjEeSVbqiFs-CnT8verXOFbvm%3Dk4OkQ%40mail.gmail.com.
Reply all
Reply to author
Forward
0 new messages