Denoising of Dynamic Contrast-enhanced Ultrasound Sequences: A Multilinear Approach.

The recent advances in three-dimensional imaging of contrast-enhanced ultrasound acquisitions enable the characterization of the tissue with a single intravenous injection of microbubbles. Many cancer markers have been extended to cover for the three-dimensional contrast ultrasound. However, most of the signal denoising algorithms do not exploit the added dimensionality and vectorize the spatial dimensions, causing a loss of information about the location of the voxels. This paper proposes a denoising algorithm based on the multilinear singular value decomposition and compares it to the singular value decomposition. The ranks are estimated based on information-theoretic criteria, and improved performance has been observed for modeling the time-intensity curves.