Conference proceeding
Real-time cardiac MRI using low-rank and sparsity penalties
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.988-991
04/2010
DOI: 10.1109/ISBI.2010.5490154
Abstract
We introduce a novel algorithm to reconstruct real-time cardiac MRI data from undersampled radial acquisitions. We exploit the fact that the spatio-temporal data can be represented as the linear combination of a few temporal basis functions. The current approaches that capitalize this property estimate the basis functions from central phase encodes, acquired with a fine temporal sampling rate. In contrast, we estimate the basis functions from the entire under-sampled data. By eliminating the need for training data, the proposed method can achieve potentially high acceleration factors. More importantly, the estimation of the temporal functions from the entire data significantly improves the quality of the basis functions, which in turn improves the quality of the reconstructions. Experiments on numerical phantoms show a significant reduction in artifacts at high acceleration factors, in comparison to current schemes.
Details
- Title: Subtitle
- Real-time cardiac MRI using low-rank and sparsity penalties
- Creators
- Sajan Goud - Dept. of Biomed. Eng., Univ. of Rochester, Rochester, NY, USAYue Hu - Dept of Electr. & Comput. Eng., Univ. of Rochester, Rochester, NY, USAMathews Jacob - Dept. of Biomed. Eng., Univ. of Rochester, Rochester, NY, USA
- Resource Type
- Conference proceeding
- Publication Details
- 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.988-991
- Publisher
- IEEE
- DOI
- 10.1109/ISBI.2010.5490154
- ISSN
- 1945-7928
- eISSN
- 1945-8452
- Language
- English
- Date published
- 04/2010
- Academic Unit
- Radiology; Iowa Neuroscience Institute; Roy J. Carver Department of Biomedical Engineering; Radiation Oncology; Electrical and Computer Engineering
- Record Identifier
- 9984070317302771
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