Clutter suppression in ultrasound: performance evaluation and review of low-rank and sparse matrix decomposition methods.

ABSTRACT: Vessel diseases are often accompanied by abnormalities related to vascular shape and size. Therefore, a clear visualization of vasculature is of high clinical significance. Ultrasound color flow imaging (CFI) is one of the prominent techniques for flow visualization. However, clutter signals originating from slow-moving tissue are one of the main obstacles to obtain a clear view of the vascular network. Enhancement of the vasculature by suppressing the clutters is a significant and irreplaceable step for many applications of ultrasound CFI. Currently, this task is often performed by singular value decomposition (SVD) of the data matrix. This approach exhibits two well-known limitations. First, the performance of SVD is sensitive to the proper manual selection of the ranks corresponding to

SUBMITTER: Zhang N 

PROVIDER: S-EPMC7254711 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature