Computer-implemented method for providing an output data set, method for determining statistical information, apparatus, computer program and data medium

An apparatus comprising:

• an input interface via which an input data set is received;
• an output interface via which an output data set is provided;
• and
• a processing facility configured to:
• generate an initial intermediate data set group from a plurality of intermediate data sets by applying a respective correction operation associated with each respective intermediate data set to the input data set, wherein the correction operation comprises one of correcting motion artifacts, metal artifacts or artifacts on the basis of high-contrast regions, beam hardening artifacts and/or scatter artifacts, a contrast optimization, or a sharpness optimization;
• order the plurality of intermediate data sets according to a quality ranking in respect of their image quality by a sorting algorithm, wherein the intermediate data sets of the initial intermediate data set group are ordered in a first iteration of a plurality of iterations, wherein, in the sorting algorithm, a relative quality metric is determined for an image quality of a first intermediate data set of the intermediate data sets in relation to a second intermediate data set of the intermediate data sets by a comparison algorithm, after which the order of the first intermediate data set and the second intermediate data set in the quality ranking is specified by a comparison of the quality metric with a quality limit value, wherein quality limit values different from one another are used in the sorting algorithm in at least two iterations and/or wherein the quality limit value is specified in at least one iteration of the plurality of iterations as a function of the input data set and/or of acquisition information relating to at least one characteristic of the acquisition of the input data set;
• form a modified intermediate data set group that comprises at least one intermediate data set which is generated by applying a correction operation dependent on the quality ranking to the input data set, after which, in a further iteration of the plurality of iterations, the ordering of the intermediate data sets are repeated;
• and
• select, after a predefined number of iterations have been performed or a convergence to an optimum has occurred, wherein the convergence may be established if the relative quality metric falls below a limit value between the first and a last intermediate data set in the quality ranking and consequently no further differences in quality between the first and last intermediate data sets may be detected, one of the intermediate data sets as a function of the quality ranking and at least one correction parameter which parameterizes a correction algorithm in order to provide the correction operation associated with the selected intermediate data set and/or the selected intermediate data set are provided as the output data set.

A non-transitory computer implemented storage medium that stores machine-readable instructions executable by at least one processor for providing an output data set based on an input data set relating to an examination subject, the machine-readable instructions comprising:

• receiving the input data set;
• generating an initial intermediate data set group from a plurality of intermediate data sets by applying a correction operation associated with an intermediate data set to the input data set;
• ordering the plurality of intermediate data sets according to a quality ranking in respect of their image quality by a sorting algorithm, wherein the intermediate data sets of the initial intermediate data set group are ordered in a first iteration of a plurality of iterations, wherein, in the sorting algorithm, a relative quality metric is determined for a relative image quality of a first intermediate data set of the intermediate data sets in relation to a second intermediate data set of the intermediate data sets by a comparison algorithm, after which the order of the respective first intermediate data set and second intermediate data set in the quality ranking is specified by a comparison of the relative quality metric with a quality limit value, wherein quality limit values that are different from one another are used in the sorting algorithm in at least two iterations and/or wherein the quality limit value is specified in at least one iteration of the plurality of iterations as a function of the input data set and/or of acquisition information relating to at least one characteristic of the acquisition of the input data set;
• forming a modified intermediate data set group that comprises at least one intermediate data set which is generated by applying a correction operation dependent on the quality ranking to the input data set, after which, in a further iteration of the plurality of iterations, the ordering of the intermediate data sets are repeated;
• selecting, after a predefined number of iterations have been performed or a convergence to an optimum has occurred, wherein the convergence may be established if the relative quality metric falls below a limit value between the first and a last intermediate data set in the quality ranking and consequently no further differences in quality between the first and last intermediate data sets may be detected when an abort condition is met, one of the intermediate data sets as a function of the quality ranking and at least one correction parameter which parameterizes a correction algorithm in order to provide the correction operation associated with the selected intermediate data set and/or the selected intermediate data set are provided as the output data set.