Key result
Novel multi-stage filtering markedly boosts microvascular ultrasound signal-to-noise and contrast ratios over standard approaches.
Why the study?
Suppression of background noise in clutter filtered contrast-free ultrasound microvasculature images is important for better visualization, accurate segmentation, and morphological analysis of vascular structures.
A novel multi-stage filtering framework significantly improves signal-to-noise and contrast-to-noise ratios in non-contrast-enhanced ultrasound microvasculature imaging.
Answers are grounded in this paper and cite their sources.
May enhance microvascular ultrasound visualization; leaves open clinical validation and outcome studies.
Suppression of background noise in clutter filtered contrast-free ultrasound microvasculature images is an important step towards better visualization, accurate segmentation, and subsequent morphological analysis of vascular structures. While different approaches to tackling this problem have been proposed, the use of denoising and vessel-enhancing filters has proven to be a straightforward and effective scheme. In this paper, we propose a multi-stage background noise removal framework, suited to microvasculature images, comprising sequential implementation of three different modes of suppressing noise and intensifying vascular patterns, namely self-similarity based collaborative filtering, mathematical morphology based denoising, and Hessian based vessel enhancement. We evaluate the effects of each filtering stage in the framework using in-vitro phantom data and compare the denoising performance of the framework with a number of existing noise removal approaches, as well as the clutter filtered images in the absence of noise suppression techniques, using in-vivo data from human subjects. The results indicate that the suggested method is, in many cases, capable of complete background noise removal, zeroing out most background regions, and improving signal-to-noise ratio and contrast-to-noise ratio in other regions by tens of dB compared to the other methods.
No takes yet. Share an insight, caveat, or question.
Sabeti et al. (2024) studied this question. Multi-stage background noise removal framework vs. Existing noise removal approaches and clutter filtered images without noise suppression was evaluated on Signal-to-noise ratio and contrast-to-noise ratio. The proposed multi-stage filtering framework improved signal-to-noise ratio and contrast-to-noise ratio by tens of dB compared to other methods in ultrasound microvasculature imaging.
Synapse has enriched 10 related papers. Consider them for comparative context: