Despeckling of Medical Ultrasound Images Based on Quantum-inspired Parameters Estimation

FU Xiao-wei; DING Ming-yue; CAI Chao; ZHOU Cheng-ping

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Despeckling of Medical Ultrasound Images Based on Quantum-inspired Parameters Estimation

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- Despeckling of Medical Ultrasound Images Based on Quantum-inspired Parameters Estimation
- Acta Electronica Sinica Vol. 39, Issue 4, Pages: 812-818(2011)
- 作者机构：
  
  1. 华中科技大学图像识别与人工智能研究所,湖北,武汉,430074
  2. 武汉科技大学计算机科学与技术学院,湖北,武汉,430065
  3. 华中科技大学生命科学与技术学院图像信息与智能控制教育部重点实验室,湖北,武汉,430074
  4. 华中科技大学图像识别与人工智能研究所湖北武汉,430074
  5. 武汉科技大学计算机科学与技术学院湖北武汉,430065
  6. 华中科技大学生命科学与技术学院图像信息与智能控制教育部重点实验室湖北武汉,430074
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.73
- Published：2011
- 稿件说明：
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FU Xiao-wei, DING Ming-yue, CAI Chao, et al. Despeckling of Medical Ultrasound Images Based on Quantum-inspired Parameters Estimation[J]. Acta Electronica Sinica, 2011, 39(4): 812-818.
DOI：

FU Xiao-wei, DING Ming-yue, CAI Chao, et al. Despeckling of Medical Ultrasound Images Based on Quantum-inspired Parameters Estimation[J]. Acta Electronica Sinica, 2011, 39(4): 812-818. DOI：

摘要

本文提出了一种基于量子衍生参数估计的医学超声图像去斑方法.通过对对数变换的超声图像小波系数建模

提出了一种带自适应参数的概率分布函数.该方法充分考虑了小波系数的尺度间相关性

利用父-子代小波系数的归一化乘积

首次在高频子带中引入量子衍生信号与噪声出现概率.并利用贝叶斯估计理论

提出了一种基于量子衍生参数估计的自适应收缩函数.实验结果表明本方法较相关算法具有更好图像细节保持能力

去斑效果显著.

Abstract

A novel despeckling method for medical ultrasound images is proposed based on quantum-inspired parameters estimation.A new probability distribution function with an adaptive parameter is built up with the modelling of log-transformed medical ultrasound images coefficients.Considering the inter-scale dependency of coefficients

the quantum-inspired probability of signal and noise is firstly introduced based on the normalized products of the coefficients and their parents.Using the Bayesian estimation theory

an adaptive shrinkage function is proposed based on quantum-inspired parameters estimation.Experiments showed that our method can notably reduce speckle noise and preserve details of medical ultrasound image effectively

which achieved much better performance than that of the other related despeckling methods.

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