What would you like to see added in this software?
PETPrep may underestimate memory for dense dynamic PET datasets, especially high-resolution 4D PET series and GTM segmentation. With Nipype MultiProc, this can allow several large nodes to run concurrently and crash with BrokenProcessPool despite a high global memory limit.
Key areas to improve:
- 4D PET reference generation and resampling
- HMC frame splitting/smoothing/thresholding
- GTM segmentation, especially with high-resolution FreeSurfer grids
Memory estimates should better reflect PET image dimensions, frame count, and anatomical/GTM grid size so scheduling is more conservative.
Do you have any interest in helping implement the feature?
Yes
Additional information / screenshots
No response
What would you like to see added in this software?
PETPrep may underestimate memory for dense dynamic PET datasets, especially high-resolution 4D PET series and GTM segmentation. With Nipype MultiProc, this can allow several large nodes to run concurrently and crash with BrokenProcessPool despite a high global memory limit.
Key areas to improve:
Memory estimates should better reflect PET image dimensions, frame count, and anatomical/GTM grid size so scheduling is more conservative.
Do you have any interest in helping implement the feature?
Yes
Additional information / screenshots
No response