tomostream is Python module for supporting streaming analysis of tomographic data where all pre-processing and reconstruction procedures are performed in real time while images are collected and the rotary stage is moving. tomostream provides this main functionality:
- Streaming reconstruction of 3 X-Y-Z ortho-slices through the sample
- The streaming reconstruction engine generates 3 selectable X-Y-Z orthogonal planes and makes them available as an EPICS PV viewable in ImageJ using the EPICS_NTNDA_Viewer plug-in. Projection, dark and flat images used for the reconstruction are taken in real time from a set of PV access variables (pvapy) and stored in a synchronized queue. On each reconstruction call new data are taken from the queue, copied to a circular GPU buffer containing projections for a 180 degrees interval, and then reconstructed.
All tomostream functionalies can be controlled from the tomoStream user interface:
Tomography instrument control
Projection, dark and flat image broadcast as PV access variables
On-demand retake of dark-flat field images
On-demand data capturing with saving in a standard hdf5 DXfile file
Set a number of projectons (“Pre count”) collected before a triggered data capturing event to be also saved in the same hdf5 file
All tomoscan_stream_2bm functionalies supporting tomostream can be controlled from the tomoScanStream user interface marked in yellow:
The output of tomostream is a live reconstruction diplaying in ImageJ using the EPICS_NTNDA_Viewer plug-in:
While the sample is rotating is possible to optimize instrument (alignment, focus, sample to detector distance etc.) and beamline (energy etc.) conditions and monitor the effect live on the 3 orthogonal slices. It is also possible to automatically trigger data capturing based on events occurring in the sample and its environment as a result of segmentation or machine learning.