Analytic heuristics for a fast DSC-MRI
About
In this paper we propose a deterministic approach for the reconstruction of Dynamic Susceptibility Contrast magnetic resonance imaging data and compare it with the compressed sensing solution existing in the literature for the same problem. Our study is based on the mathematical analysis of the problem, which is computationally intractable because of its non polynomial complexity, but suggests simple heuristics that perform quite well. We give results on real images and on artificial phantoms with added noise.
Marco Virgulin, Marco Castellaro, Enrico Grisan, Fabio Marcuzzi• 2018
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Signal Reconstruction | Real DSC-MRI dataset | Relative Percentage Error0.45 | 24 | |
| Image Reconstruction | Simulated dataset | Relative Percent Error0.7 | 23 | |
| Image Reconstruction | Simulated dataset (with noise) SNR 15 dB | Relative Percent Error1.01 | 23 |
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