Hi CASToR community,
I recently read a paper on PET image reconstruction using voxelized phantoms in GATE and CASToR (PET image reconstruction and dosimetry from voxelized phantoms with GATE - ScienceDirect), where they discussed applying data corrections, including attenuation, random, scatter, and normalization, before reconstruction.
I’d like to implement these same corrections in my own study to analyze their impact on the final reconstructed images. However, I’m finding it challenging to understand the practical steps involved, particularly for the normalization correction.
I reviewed the reference article they followed (Normalization of Monte Carlo PET data using GATE | IEEE Conference Publication | IEEE Xplore) and understood that calculating normalization coefficients requires two simulations: one with a cylindrical volume source and another with a cylindrical surface source. While I think I’ve grasped the theoretical approach, I’m struggling with how to set up and execute these simulations in GATE and then compute the normalization factors.
If anyone has experience with this process, could you please share a step-by-step guide or tips on how to set up the simulations in GATE and compute afterwards the normalization values?
I’d be extremely grateful for any guidance you can provide.
Thank you!
Greetings,
Beatriz