User-Guided Compressed Sensing for Magnetic Resonance Angiography

Compressed sensing (CS) magnetic resonance imaging (MRI) enables the reconstruction of MRI images with fewer samples in k-space. One requirement is that the acquired image has a sparse representation in a known transform domain. MR angiograms are already sparse in the image domain. They can be further sparsified through finitedifferences. Therefore, it is a natural application for CSMRI. However, low-contrast vessels are likely to disappear at high undersampling ratios, since the commonly used `1 reconstruction tends to underestimate the magnitude of the transformed sparse coefficients. These vessels, however, are likely to be clinically important for medical diagnosis. To avoid the fading of low-contrast vessels, we propose a user-guided CS MRI that is able to mitigate the reduction of vessel contrast within a region of interest (ROI). Simulations show that these low-contrast vessels can be well maintained via our method which results in higher local quality compared to conventional CS.

@InProceedings { ZVEV14,
  author       = "Zhang, Changgong and Giessen, Martijn van de and Eisemann, Elmar and Vilanova, Anna",
  title        = "User-Guided Compressed Sensing for Magnetic Resonance Angiography",
  booktitle    = "36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014)",
  year         = "2014",
  url          = "http://graphics.tudelft.nl/Publications-new/2014/ZVEV14"
}