Data Collection

TomoScan

The tomography scans are managed by tomoScan [TXM5]. Please refer to the tomoScan documentation for details.

To configure a single tomographic scan enter the acquistion parameters at:

tomoScan

Streaming data collection

tomoScan provides also support for streaming data collection[TXM5] (see tomoScanStream documentation for details). When collecting data in streaming mode, projections, dark and flat images are broadcasted using PVaccess and can be retrieved as EPICS PVs.

Streaming data collection features are:

  1. Projection, dark and flat image broadcast as PV access variables

  2. On-demand retake of dark-flat field images

  3. On-demand data capturing with saving in a standard Data Exchange hdf5file

  4. Set a number of projectons (“Pre count”) collected before a triggered data capturing event to be also saved in the same hdf5 file

All TomoScanStream functionalies can be controlled from the Streaming Control section of:

../../../_images/tomoScanStream.png

Streaming data reconstruction

The projection, dark and flat image broadcast provided by tomoScanStream can be used to reconstruct in real-time 3 orthogonal slices. This task is accomplished by tomoStream.

Streaming data reconstruction features are:

  1. Streaming reconstruction of 3 (X-Y-Z) ortho-slices through the sample

  2. On demand adjustment of the

    • X Y Z ortho-slice positions

    • reconstruction rotation center

    • reconstruction filter

All tomoStream functionalies can be controlled from the tomoStream user interface:

../../../_images/tomoStream.png

The output of tomostream is a live reconstruction diplaying in ImageJ using the EPICS_NTNDA_Viewer plug-in:

../../../_images/tomoStreamRecon.png

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.