Further development of image reconstruction from highly undersampled (k, t)-space data with joint partial separability and sparsity constraints

Bo Zhao, Justin P. Haldar, Anthony G. Christodoulou, Zhi-Pei Liang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Joint use of partial separability (PS) and spatial-spectral sparsity constraints has previously been demonstrated useful for image reconstruction from undersampled data. This paper extends our early work in this area by proposing a new method for jointly enforcing the PS and spatial total variation (TV) constraints for dynamic MR image reconstruction. An algorithm is also described to solve the underlying optimization problem efficiently. The proposed method has been validated using simulated cardiac imaging data, with the expected capability to reduce image artifacts and reconstruction noise.

Original languageEnglish (US)
Title of host publication2011 8th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI'11
Pages1593-1596
Number of pages4
DOIs
StatePublished - 2011
Event2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 - Chicago, IL, United States
Duration: Mar 30 2011Apr 2 2011

Other

Other2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11
CountryUnited States
CityChicago, IL
Period3/30/114/2/11

Fingerprint

Computer-Assisted Image Processing
Image reconstruction
Joints
Imaging techniques
Artifacts
Noise

Keywords

  • Dynamic MRI
  • Half-quadratic Regularization
  • Low-rank Matrices
  • Partial Separability
  • Sparsity
  • Total Variation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Zhao, B., Haldar, J. P., Christodoulou, A. G., & Liang, Z-P. (2011). Further development of image reconstruction from highly undersampled (k, t)-space data with joint partial separability and sparsity constraints. In 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 (pp. 1593-1596). [5872707] https://doi.org/10.1109/ISBI.2011.5872707

Further development of image reconstruction from highly undersampled (k, t)-space data with joint partial separability and sparsity constraints. / Zhao, Bo; Haldar, Justin P.; Christodoulou, Anthony G.; Liang, Zhi-Pei.

2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11. 2011. p. 1593-1596 5872707.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhao, B, Haldar, JP, Christodoulou, AG & Liang, Z-P 2011, Further development of image reconstruction from highly undersampled (k, t)-space data with joint partial separability and sparsity constraints. in 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11., 5872707, pp. 1593-1596, 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11, Chicago, IL, United States, 3/30/11. https://doi.org/10.1109/ISBI.2011.5872707
Zhao B, Haldar JP, Christodoulou AG, Liang Z-P. Further development of image reconstruction from highly undersampled (k, t)-space data with joint partial separability and sparsity constraints. In 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11. 2011. p. 1593-1596. 5872707 https://doi.org/10.1109/ISBI.2011.5872707
Zhao, Bo ; Haldar, Justin P. ; Christodoulou, Anthony G. ; Liang, Zhi-Pei. / Further development of image reconstruction from highly undersampled (k, t)-space data with joint partial separability and sparsity constraints. 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11. 2011. pp. 1593-1596
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