Expectation Maximization for Joint Deconvolution and Statistics Estimation

被引：4

作者：

Alessandrini, M. ^{[1
]}

Palladini, A. ^{[1
]}

De Marchi, L. ^{[1
]}

Speciale, N. ^{[1
]}

机构：

[1] Univ Bologna, ARCES DEIS, I-40136 Bologna, Italy

来源：

ACOUSTICAL IMAGING, VOL 30 | 2011年 / 30卷

关键词：

Deconvolution; Expectation maximization; Generalized gaussian distribution; ULTRASOUND IMAGES; BLIND DECONVOLUTION; MEDICAL ULTRASOUND; RESTORATION; ALGORITHM; MODEL;

D O I：

10.1007/978-90-481-3255-3_38

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

Biomedical ultrasound image quality is limited due to the blurring of tissue reflectivity introduced by the transducer Point Spread Function (PSF). Deconvolution techniques can be used to obtain the pure tissue response, otherwise called reflectivity function. Typically deconvolution methods are developed in the only purpose of image visual quality improvement. In this work we present an Expectation Maximization (EM) framework for US images deconvolution in which local statistical description of the tissue reflectivity is restored as well, so that features extracted from the deconvolved frame can theoretically be used for classification purposes.

引用

页码：335 / 343

页数：9

共 15 条

[1]

[Anonymous], J ROYAL STAT SOC B

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