MRF denoising with compressed sensing and adaptive filtering
pith:BT7R3ADO Add to your LaTeX paper
What is a Pith Number?\usepackage{pith}
\pithnumber{BT7R3ADO}
Prints a linked pith:BT7R3ADO badge after your title and writes the identifier into PDF metadata. Compiles on arXiv with no extra files. Learn more
read the original abstract
The recently proposed Magnetic Resonance Fingerprinting (MRF) technique can simultaneously estimate multiple parameters through dictionary matching. It has promising potentials in a wide range of applications. However, MRF introduces errors due to undersampling during the data acquisition process and the limit of dictionary resolution. In this paper, we investigate the error source of MRF and propose the technologies of improving the quality of MRF with compressed sensing, error prediction by decision trees, and adaptive filtering. Experimental results support our observations and show significant improvement of the proposed technologies.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.