Ultrasound Speckle Reduction Based on Histogram Curve Matching and Region Growing
CMC-COMPUTERS MATERIALS & CONTINUA(2020)
摘要
The quality of ultrasound scanning images is usually damaged by speckle noise. This paper proposes a method based on local statistics extracted from a histogram to reduce ultrasound speckle through a region growing algorithm. Unlike single statistical moment-based speckle reduction algorithms, this method adaptively smooths the speckle regions while preserving the margin and tissue structure to achieve high detectability. The criterion of a speckle region is defined by the similarity value obtained by matching the histogram of the current processing window and the reference window derived from the speckle region in advance. Then, according to the similarity value and tissue characteristics, the entire image is divided into several levels of speckle-content regions, and adaptive smoothing is performed based on these classification characteristics and the corresponding window size determined by the proposed region growing technique. Tests conducted from phantoms and in vivo images have shown very promising results after a quantitative and qualitative comparison with existing work.
更多查看译文
关键词
Ultrasound speckle,histogram matching,speckle reduction,tissue characterization,region growing
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要