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双TranSpeckle:基于双通道变压器的编码器-解码器网络用于医疗超声波图像除斑

Yuqing Chen¹, Zhitao Guo², Jinli Yuan¹

¹School of Electronic and Information Engineering, Hebei University of Technology, Tianjin, 300401, China.

Computers in biology and medicine

|March 26, 2024

概括

双TranSpeckle (DTS) 是一个新的深度学习网络,用于医疗超声波图像脱光. 它使用双路变压器有效地抑制斑点噪声,同时保留关键的图像结构.

科学领域:

医疗成像医学成像
深度学习 (Deep Learning) 是一种深度学习.
图像处理图像处理

背景情况:

现有的深度学习解密算法往往忽略了语义和像素特征之间的区别.
这种限制影响了处理复杂的医学超声波图像的有效性.

研究的目的:

介绍双TranSpeckle (DTS),一个新的双路径变压器网络,用于增强医疗超声波图像脱光.
为了改善压制斑点噪声,同时保持精细的图像细节和结构.

主要方法:

DTS网络采用双路径变压器架构,具有单独的"语义"和"像素"路径.
关键模块包括语义块,双块和合并块,利用变压器架构进行特征提取和交互.
信息通过语义和像素路径并行处理,以捕获全球和本地图像特征.

主要成果:

DTS在包括峰值信号与噪声比率 (PSNR),结构相似性 (SSIM),特征相似性 (FSIM) 和自然性图像质量评估器 (NIQE) 在内的定量指标中取得了显著改善.
定性分析证实了除性能的大幅提高,有效地减少了斑点噪声.
基本的图像结构被保存得很好,这表明没有斑点的图像具有高保真性.

结论:

拟议的双TranSpeckle (DTS) 网络为医疗超声波图像脱光提供了一种优越的方法.
双路径的变压器架构有效地平衡了语义和像素级特征的处理.
DTS显示了提高超声波图像诊断质量的巨大潜力.

关键词:

清除斑点的噪音可以听到.这是一个双TranSpecklele.双路径的双路径.变压器变压器变压器超声波图像超声波图像超声波图像

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