Infimal Convolution of Total Generalized Variation Functionals (ICTGV) for dynamic MRI

Research output: Contribution to conferenceAbstractResearchpeer-review

Abstract

The concept of ICTGV provides a
suitable regularisation strategy to stabilize the
reconstruction of images sequences from
incomplete and noisy MR data. It is successfully applied in the context of dynamic MRI applications to enable a further increase of
desired higher spatial and temporal resolution
and spatial coverage for cine cardiac imaging,
DCE-MRI or quantitative MRI. It furthermore
provides a new approach for local
decomposition into components with slower
and faster temporal dynamics.

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Fields of Expertise

  • Human- & Biotechnology

Cite this

Schlögl, M., Holler, M., Bredies, K., & Stollberger, R. (2017). Infimal Convolution of Total Generalized Variation Functionals (ICTGV) for dynamic MRI. Abstract from 20. Jahrestagung der Deutschen Sektion der ISMRM, Göttingen, Germany.

Infimal Convolution of Total Generalized Variation Functionals (ICTGV) for dynamic MRI. / Schlögl, Matthias; Holler, Martin; Bredies, Kristian; Stollberger, Rudolf.

2017. Abstract from 20. Jahrestagung der Deutschen Sektion der ISMRM, Göttingen, Germany.

Research output: Contribution to conferenceAbstractResearchpeer-review

Schlögl, M, Holler, M, Bredies, K & Stollberger, R 2017, 'Infimal Convolution of Total Generalized Variation Functionals (ICTGV) for dynamic MRI' 20. Jahrestagung der Deutschen Sektion der ISMRM, Göttingen, Germany, 7/09/17 - 9/09/17, .
Schlögl M, Holler M, Bredies K, Stollberger R. Infimal Convolution of Total Generalized Variation Functionals (ICTGV) for dynamic MRI. 2017. Abstract from 20. Jahrestagung der Deutschen Sektion der ISMRM, Göttingen, Germany.
Schlögl, Matthias ; Holler, Martin ; Bredies, Kristian ; Stollberger, Rudolf. / Infimal Convolution of Total Generalized Variation Functionals (ICTGV) for dynamic MRI. Abstract from 20. Jahrestagung der Deutschen Sektion der ISMRM, Göttingen, Germany.
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abstract = "The concept of ICTGV provides a suitable regularisation strategy to stabilize the reconstruction of images sequences from incomplete and noisy MR data. It is successfully applied in the context of dynamic MRI applications to enable a further increase of desired higher spatial and temporal resolution and spatial coverage for cine cardiac imaging, DCE-MRI or quantitative MRI. It furthermore provides a new approach for local decomposition into components with slower and faster temporal dynamics.",
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