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Found 9 papers, 2 papers with code
Ultrasound Imaging based on the Variance of a Diffusion Restoration Model
Despite today's prevalence of ultrasound imaging in medicine, ultrasound signal-to-noise ratio is still affected by several sources of noise and artefacts.
Diffusion Reconstruction of Ultrasound Images with Informative Uncertainty
Bringing the best from both worlds, we propose a hybrid approach leveraging advances in diffusion models.
Ultrasound Image Reconstruction with Denoising Diffusion Restoration Models
Ultrasound image reconstruction can be approximately cast as a linear inverse problem that has traditionally been solved with penalized optimization using the $l_1$ or $l_2$ norm, or wavelet-based terms.
A Partially Collapsed Sampler for Unsupervised Nonnegative Spike Train Restoration
In this paper the problem of restoration of non-negative sparse signals is addressed in the Bayesian framework.
SLS (Single $\ell_1$ Selection): a new greedy algorithm with an $\ell_1$-norm selection rule
In this paper, we propose a new greedy algorithm for sparse approximation, called SLS for Single L_1 Selection.
Local-mean preserving post-processing step for non-negativity enforcement in PET imaging: application to $^{90}$Y-PET
Our idea is to transfer the negative intensities to neighboring voxels, so that the mean of the image is preserved.
Multiplicative Updates for NMF with $β$-Divergences under Disjoint Equality Constraints
In this paper, we introduce a general framework to design multiplicative updates (MU) for NMF based on $\beta$-divergences ($\beta$-NMF) with disjoint equality constraints, and with penalty terms in the objective function.
Homotopy based algorithms for $\ell_0$-regularized least-squares
Among the many efficient $\ell_1$ solvers, the homotopy algorithm minimizes $\|y-Ax\|_2^2+\lambda\|x\|_1$ with respect to x for a continuum of $\lambda$'s.
Algorithms for nonnegative matrix factorization with the beta-divergence
The paper also describes how the proposed algorithms can be adapted to two common variants of NMF : penalized NMF (i. e., when a penalty function of the factors is added to the criterion function) and convex-NMF (when the dictionary is assumed to belong to a known subspace).
