Blind Deconvolution for Ultrasound Sequences Using a Noninverse Greedy Algorithm
Author(s) -
Liviu-Teodor Chira,
Corneliu Rusu,
Clovis Tauber,
JeanMarc Girault
Publication year - 2013
Publication title -
international journal of biomedical imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.626
H-Index - 41
eISSN - 1687-4196
pISSN - 1687-4188
DOI - 10.1155/2013/496067
Subject(s) - deconvolution , blind deconvolution , algorithm , computer science , wiener deconvolution , greedy algorithm , speckle pattern , speckle noise , point spread function , signal (programming language) , artificial intelligence , mathematics , programming language
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.
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