Incorporation of prior knowledge in compressed sensing for faster acquisition of hyperpolarized gas images
| Autor: | Salma Ajraoui, Juan Parra-Robles, Jim M. Wild |
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| Rok vydání: | 2011 |
| Předmět: |
Adult
Male Computer science Contrast Media Iterative reconstruction Helium Sensitivity and Specificity Root mean square Isotopes Image Interpretation Computer-Assisted Humans Radiology Nuclear Medicine and imaging Computer vision Lung region Lung ventilation Lung Prior information business.industry Reproducibility of Results Data Compression Image Enhancement Magnetic Resonance Imaging Compressed sensing Square error Female Artificial intelligence Gases Radiopharmaceuticals business Algorithms |
| Zdroj: | Magnetic resonance in medicine. 69(2) |
| ISSN: | 1522-2594 |
| Popis: | Adding prior knowledge to compressed sensing reconstruction can improve image reconstruction. In this work, two approaches are investigated to improve reconstruction of two-dimensional hyperpolarized 3He lung ventilation images using prior knowledge. When compared against a standard compressed sensing reconstruction, the proposed methods allowed acquisition of images with higher under-sampling factors and reduction of the blurring effects that increase with higher reduction factors when fixed flip angles are used. These methods incorporate the prior knowledge of polarization decay of hyperpolarized 3He and the mutual anatomical information from a registered 1H image acquired in the same breath. Three times accelerated two-dimensional images reconstructed with compressed sensing and prior knowledge gave lower root-mean square error, than images reconstructed without introduction of any prior information. When introducing the polarization decay as prior knowledge, a significant improvement was achieved in the lung region, the root mean square value decreased by 45% and from the whole image by 36%. When introducing the mutual anatomical information as prior knowledge, the root mean square decreased by 21% over the lung region and by 15% over the whole image. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc. |
| Databáze: | OpenAIRE |
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