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Compressed sensing reconstruction of 7 Tesla 23Na multi-channel breast data using 1H MRI constraint.
Lachner, Sebastian; Zaric, Olgica; Utzschneider, Matthias; Minarikova, Lenka; Zbýn, Stefan; Hensel, Bernhard; Trattnig, Siegfried; Uder, Michael; Nagel, Armin M.
Afiliación
  • Lachner S; Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany. Electronic address: sebastian.lachner@uk-erlangen.de.
  • Zaric O; High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Utzschneider M; Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
  • Minarikova L; High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Zbýn S; High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA.
  • Hensel B; Center for Medical Physics and Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
  • Trattnig S; High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Uder M; Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
  • Nagel AM; Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany; Division of Medical Physics in Radiology, German Cancer Research Centre (DKFZ), Heidelberg, Germany; Institute of Medical Physics, Friedrich-Alexander-Universität Erlange
Magn Reson Imaging ; 60: 145-156, 2019 07.
Article en En | MEDLINE | ID: mdl-30943437
ABSTRACT

PURPOSE:

To reduce acquisition time and to improve image quality in sodium magnetic resonance imaging (23Na MRI) using an iterative reconstruction algorithm for multi-channel data sets based on compressed sensing (CS) with anatomical 1H prior knowledge.

METHODS:

An iterative reconstruction for 23Na MRI with multi-channel receiver coils is presented. Based on CS it utilizes a second order total variation (TV(2)), adopted by anatomical weighting factors (AnaWeTV(2)) obtained from a high-resolution 1H image. A support region is included as additional regularization. Simulated and measured 23Na multi-channel data sets (n = 3) of the female breast acquired at 7 T with different undersampling factors (USF = 1.8/3.6/7.2/14.4) were reconstructed and compared to a conventional gridding reconstruction. The structural similarity was used to assess image quality of the reconstructed simulated data sets and to optimize the weighting factors for the CS reconstruction.

RESULTS:

Compared with a conventional TV(2), the AnaWeTV(2) reconstruction leads to an improved image quality due to preserving of known structure and reduced partial volume effects. An additional incorporated support region shows further improvements for high USFs. Since the decrease in image quality with higher USFs is less pronounced compared to a conventional gridding reconstruction, proposed algorithm is beneficial especially for higher USFs. Acquisition time can be reduced by a factor of 4 (USF = 7.2), while image quality is still similar to a nearly fully sampled (USF = 1.8) gridding reconstructed data set.

CONCLUSION:

Especially for high USFs, the proposed algorithm allows improved image quality for multi-channel 23Na MRI data sets.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Mama / Imagen por Resonancia Magnética Tipo de estudio: Prognostic_studies Límite: Adult / Female / Humans Idioma: En Revista: Magn Reson Imaging Año: 2019 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Mama / Imagen por Resonancia Magnética Tipo de estudio: Prognostic_studies Límite: Adult / Female / Humans Idioma: En Revista: Magn Reson Imaging Año: 2019 Tipo del documento: Article