Basic Concepts

Basic Concepts

Meta data

Meta data record of the Flexbox contains three sections: geometry, settings and description.

The geometry section is the most essential one and can be of different types, depending on the complexity of the scanning. Currently implemented types are:

• simple
• static_offsets
• linear_offsets

The simple type contains the minimum number of records needed to reconstruct a typical CT dataset: units, pixel and sizes, distances (SOD, SDD), ranges (angular).

In the static_offsets type we add records that correspond to the static offsets applied to the source, object and detector positions.

In the linear_offsets type each record has two values - at the beginning of the scan and at the end of the scan. Values are assumed to change linearly in-between.

When the reconstruction is finished, the meta data can be saved.

Data

Data in Flexbox is typically loaded from the disk to a numpy array in the RAM memory or mapped on a fast disk (e.g. SSD). When batch processing scripts are made, to make sure that the memory is freed, we recommend to use Python with statement:

with flexbox.data.data('C:\Data\my_scan') as data: