 Motion Compensation Strategies in TomographyBernadette N. Hahn ()
A chapter in Time-dependent Problems in Imaging and Parameter Identification, 2021, pp 51-83 from Springer Abstract: Abstract Imaging modalities have been developed and established as important and powerful tools to recover characteristics of the interior structure of a studied specimen from induced measurements. The reconstruction process constitutes a well-known application of the theory of inverse problems and is well understood if the investigated object is stationary. However, in many medical and industrial applications, the studied quantity shows a time-dependency, for instance due to patient or organ motion. Most imaging modalities record the data sequentially, i.e. temporal changes of the object during the measuring process lead to inconsistent data sets. Therefore, standard reconstruction techniques which solve the underlying inverse problem in the static case lead to motion artefacts in the computed image and hence to a degraded image quality. Consequently, suitable models and algorithms with a specific treatment of the dynamics have to be developed in order to solve such time-dependent imaging problems. This article provides a respective theoretical framework as well as numerical results from different imaging applications, including a study of 3D cone-beam CT. Date: 2021 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-57784-1_3 Ordering information: This item can be ordered from DOI: 10.1007/978-3-030-57784-1_3 Access Statistics for this chapter More chapters in Springer Books from Springer |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.