Real time ultrasound image denoising

被引：55

作者：

de Fontes, Fernanda Palhano Xavier ^{[1
]}

Barroso, Guillermo Andrade ^{[1
]}

Coupe, Pierrick ^{[1
]}

Hellier, Pierre ^{[1
]}

机构：

[1] INRIA Ctr Rech Rennes Bretagne Atlantique, F-35042 Rennes, France

来源：

JOURNAL OF REAL-TIME IMAGE PROCESSING | 2011年 / 6卷 / 01期

关键词：

Image denoising; Ultrasound imaging; Non-local means; GPGPU; SPECKLE SUPPRESSION; EDGE-DETECTION; FILTER; NOISE; SEGMENTATION;

D O I：

10.1007/s11554-010-0158-5

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Image denoising is the process of removing the noise that perturbs image analysis methods. In some applications like segmentation or registration, denoising is intended to smooth homogeneous areas while preserving the contours. In many applications like video analysis, visual servoing or image-guided surgical interventions, real-time denoising is required. This paper presents a method for real-time denoising of ultrasound images: a modified version of the NL-means method is presented that incorporates an ultrasound dedicated noise model, as well as a GPU implementation of the algorithm. Results demonstrate that the proposed method is very efficient in terms of denoising quality and is real-time.

引用

页码：15 / 22

页数：8

共 29 条

[21]

Motwani M.C., 2004, P GSPX, V27, P27

[22] An iterative regularization method for total variation-based image restoration [J].

Osher, S ;

Burger, M ;

Goldfarb, D ;

Xu, JJ ;

Yin, WT .

MULTISCALE MODELING & SIMULATION, 2005, 4 (02) :460-489

[23] SCALE-SPACE AND EDGE-DETECTION USING ANISOTROPIC DIFFUSION [J].

PERONA, P ;

MALIK, J .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1990, 12 (07) :629-639

[24] NONLINEAR TOTAL VARIATION BASED NOISE REMOVAL ALGORITHMS [J].

RUDIN, LI ;

OSHER, S ;

FATEMI, E .

PHYSICA D, 1992, 60 (1-4) :259-268

[25] A multiscale image representation using hierarchical (BV, L2) decompositions [J].

Tadmor, E ;

Nezzar, S ;

Vese, L .

MULTISCALE MODELING & SIMULATION, 2004, 2 (04) :554-579

[26] Evaluation of four probability distribution models for speckle in clinical cardiac ultrasound images [J].

Tao, Zhong ;

Tagare, Hemant D. ;

Beaty, James D. .

IEEE TRANSACTIONS ON MEDICAL IMAGING, 2006, 25 (11) :1483-1491

[27]

Tay PC, 2006, I S BIOMED IMAGING, P221

[28] Ultrasound despeckling using an adaptive window stochastic approach [J].

Tay, Peter C. ;

Acton, Scott T. ;

Hossack, John A. .

2006 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2006, PROCEEDINGS, 2006, :2549-+

[29] Classification and estimation of ultrasound speckle noise with neural networks [J].

Wachowiak, MP ;

Smolikova, R ;

Elmaghraby, AS ;

Zurada, JM .

IEEE INTERNATIONAL SYMPOSIUM ON BIO-INFORMATICS AND BIOMEDICAL ENGINEERING, PROCEEDINGS, 2000, :245-252

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