Decompression and speckle detection for ultrasound images using the homodyned K-distribution

Authors:
R. W. Prager;A. H. Gee;G. M. Treece;L. H. Berman
Affiliations:
Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK;Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK;Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK;Department of Radiology, University of Cambridge, Level 5, Box 219, Addenbrooke's Hospital Hills Road, Cambridge CB2 2QQ UK
Venue:
Pattern Recognition Letters - Speciqal issue: Ultrasonic image processing and analysis
Year:
2003

Citing 1
Cited 6

Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,

Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,

A diffusion stick method for speckle suppression in ultrasonic images

Pattern Recognition Letters
Learning a tissue invariant ultrasound speckle decorrelation model

ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Probabilistic speckle decorrelation for 3D ultrasound

MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
On estimating de-speckled and speckle components from B-mode ultrasound images

ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Measurement selection in untracked freehand 3D ultrasound

MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
Real-Time quality control of tracked ultrasound

MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

The ultrasound envelope intensity distribution can be used for speckle detection and for measuring the distance between images by speckle decorrelation. However, this intensity signal is rarely available. Many researchers work with B-scan data which has been scan-converted and subject to nonlinear mappings to compress the dynamic range. This paper presents an approximate algorithm for recovering the intensity signal from B-scan data. It is then used as the basis of a speckle detector using the statistics of a homodyned k-distribution.