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To Image Analysis in Computed Tomography
The presence of errors in tomographic image may lead to misdiagnosis when computed tomography (CT) is used
in medicine, or the wrong decision about parameters of technological processes when CT is used in the industrial
applications. Two main reasons produce these errors. First, the errors occur on the step corresponding to
the measurement, e.g. incorrect calibration and estimation of geometric parameters of the set-up. The second
reason is the nature of the tomography reconstruction step. At the stage a mathematical model to calculate
the projection data is created. Applied optimization and regularization methods along with their numerical
implementations of the method chosen have their own specific errors. Nowadays, a lot of research teams try to
analyze these errors and construct the relations between error sources. In this paper, we do not analyze the
nature of the final error, but present a new approach for the calculation of its distribution in the reconstructed
volume. We hope that the visualization of the error distribution will allow experts to clarify the medical report
impression or expert summary given by them after analyzing of CT results. To illustrate the efficiency of the
proposed approach we present both the simulation and real data processing results.