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Region‐of‐interest tomography using filtered backprojection: assessing the practical limits
Author(s) -
KYRIELEIS A.,
TITARENKO V.,
IBISON M.,
CONNOLLEY T.,
WITHERS P.J.
Publication year - 2011
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/j.1365-2818.2010.03408.x
Subject(s) - image stitching , pixel , truncation (statistics) , projection (relational algebra) , sample (material) , computer science , artificial intelligence , computer vision , iterative reconstruction , range (aeronautics) , region of interest , resolution (logic) , detector , feature (linguistics) , algorithm , physics , telecommunications , linguistics , philosophy , materials science , machine learning , composite material , thermodynamics
Summary There are many cases where it is desirable to reconstruct at high resolution a small volume from a larger sample. Here we describe the outcomes of a reconstruction trial based on real samples aimed at delineating the practical limits to which a small region of interest can be viewed from a large sample. Our approach has been to artificially truncate the sinograms of whole sample scans to simulate region of interest tomography. A simple filtered back projection algorithm has been applied, with the sinograms extended laterally in a simple manner to make up for the truncated portions. The impact of the degree of truncation (from 0% down to 99%), the number of projections used, as well as the position of the region of interest, on the faithfulness of the reconstruction is evaluated for a range of sample types. We have assessed the nature of, and extent to which, artefacts are introduced and the degree to which simple strategies can minimize them to an acceptable level without the need for complex reconstruction algorithms, projection stitching strategies or very large detectors. It is found that for a wide range of objects the effect of truncation on feature detection is negligible and that excellent images can be reconstructed if the number of projections is calculated not on the basis of the number of pixels on the camera, but on the number of pixels that would be required to scan the whole sample at the chosen pixel resolution. This paper demonstrates that in many cases more sophisticated reconstruction strategies are not necessary.