Chira Liviu-Teodor, Rusu Corneliu, Tauber Clovis, Girault Jean-Marc
Signal & Imaging Group, University François Rabelais of Tours, PRES Loire Valley University, UMR INSERM U930, 7 Avenue Marcel Dassault, 37200 Tours Cedex, France ; Faculty of Electronics, Telecommunications and Information Theory, Technical University of Cluj-Napoca, Cluj-Napoca 400027, Romania.
Faculty of Electronics, Telecommunications and Information Theory, Technical University of Cluj-Napoca, Cluj-Napoca 400027, Romania.
Int J Biomed Imaging. 2013;2013:496067. doi: 10.1155/2013/496067. Epub 2013 Dec 29.
The blind deconvolution of ultrasound sequences in medical ultrasound technique is still a major problem despite the efforts made. This paper presents a blind noninverse deconvolution algorithm to eliminate the blurring effect, using the envelope of the acquired radio-frequency sequences and a priori Laplacian distribution for deconvolved signal. The algorithm is executed in two steps. Firstly, the point spread function is automatically estimated from the measured data. Secondly, the data are reconstructed in a nonblind way using proposed algorithm. The algorithm is a nonlinear blind deconvolution which works as a greedy algorithm. The results on simulated signals and real images are compared with different state of the art methods deconvolution. Our method shows good results for scatters detection, speckle noise suppression, and execution time.
尽管已做出诸多努力，但医学超声技术中超声序列的盲反卷积仍是一个主要问题。本文提出一种盲非逆反卷积算法，利用采集到的射频序列包络和反卷积信号的先验拉普拉斯分布来消除模糊效应。该算法分两步执行。首先，从测量数据中自动估计点扩散函数。其次，使用所提出的算法以非盲方式重建数据。该算法是一种非线性盲反卷积，作为一种贪婪算法运行。将模拟信号和真实图像上的结果与不同的现有先进反卷积方法进行了比较。我们的方法在散射体检测、斑点噪声抑制和执行时间方面显示出良好的结果。
