Analytic heuristics for a fast DSC-MRI
This work addresses a domain-specific problem in medical imaging by providing a faster alternative for DSC-MRI reconstruction, but it is incremental as it builds on existing methods without a major breakthrough.
The authors tackled the computationally intractable reconstruction of Dynamic Susceptibility Contrast MRI data by proposing deterministic heuristics based on mathematical analysis, achieving competitive performance compared to existing compressed sensing methods as demonstrated on real images and artificial phantoms with noise.
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.