Abstract
Introduction:The quantitative assessment of MR parameters like T1, T2, ADC, etc. requires the acquisition of multiple images of the sameanatomy, which results in long scan times. However, these data can be described by a model with only a few parameters and in that sense they arehighly compressible. Thus, Compressed Sensing (CS) could be applied toaccelerate the data acquisition. In this work we introduce a model-basedreconstruction from undersampled data, which performs simultaneous imagereconstruction and parameter mapping and demonstrate it for the example of T1mapping.
| Original language | English |
|---|---|
| Pages | 2295-2295 |
| Number of pages | 1 |
| Publication status | Published - 01.04.2009 |
| Event | 17th Meeting of the International Society for Magnetic Resonance in Medicine - Honolulu, United States Duration: 18.04.2009 → 24.04.2009 https://www.ismrm.org/09/ |
Conference
| Conference | 17th Meeting of the International Society for Magnetic Resonance in Medicine |
|---|---|
| Abbreviated title | ISMRM 2009 |
| Country/Territory | United States |
| City | Honolulu |
| Period | 18.04.09 → 24.04.09 |
| Internet address |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
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