I’m looking to calculate SNR (yes, I know it’s not the best means of getting this sort of metric) as SNR=meanSignal/SDNoise but I’m having trouble figuring out how to estimate the background (black) portion of the image whilst excluding anatomy. Thank you in advance!
You may directly use this tool: MRIQC, or directly look at how they implemented their SNR calculations:
Hi, thank you for the comment! I have been playing with MRIQC, but I’m not looking to run the whole program, and I’m unsure as to how to use the snr() and cnr() method in isolation.
From what I understand, you will need to get two masks for your image: the mask of your object and the mask for the background. For the background mask (air mask) it looks like the code for MRIQC is the following:
This implementation is derived from the work presented here:
yes you will nee at least two mask. For the background one you want to avoid some aliasing signal (due to motion) in the phase direction. so you may want to design a “hat” mask
Then to get the mean (in the tissue mask) you may want to remove Intensity biais first …
so you will end up doing several steps from the mriqc pipeline … so why not go with it ?