Dynamic MRI reconstruction using low rank plus sparse tensor decomposition
| Autor: | Dornoosh Zonoobi, Jacob L. Jaremko, Shahrooz Faghih Roohi, Ashraf A. Kassim |
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| Rok vydání: | 2016 |
| Předmět: |
Rank (linear algebra)
business.industry 02 engineering and technology Iterative reconstruction Reconstruction method 030218 nuclear medicine & medical imaging Matrix decomposition 03 medical and health sciences 0302 clinical medicine Dynamic contrast-enhanced MRI 0202 electrical engineering electronic engineering information engineering Tensor decomposition 020201 artificial intelligence & image processing Computer vision Minification Artificial intelligence Mr images business Algorithm Mathematics |
| Zdroj: | ICIP |
| DOI: | 10.1109/icip.2016.7532662 |
| Popis: | In this paper, we introduce a multi-dimensional approach to the problem of reconstruction of MR image sequences that are highly undersampled in k-space. By formulating the reconstruction as a high-order low-rank plus sparse tensor decomposition problem, we propose an efficient numerical algorithm based on the alternating direction method of multipliers (ADMM) to solve the optimization. Through extensive experimental results we show that our proposed method achieves superior reconstruction quality, compared to the state-of-the-art reconstruction methods. |
| Databáze: | OpenAIRE |
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