Name
Title | ||
|---|---|---|
Segmentation of echocardiographic images based on statistical modelling of the radio-frequency signal |
Abstract | ||
|---|---|---|
This work presents an algorithm for segmentation of ultrasound images based on the statistics of the radio-frequency (RF) signal. We first show that the Generalized Gaussian distribution can reliably model both fully (blood pool) and partially (tissue area) developed speckle in echocardiographic RF images. We then show that this probability density function (pdf) may be used in a maximum likelihood framework for tissue segmentation. Results are presented on both simulations and ultrasound cardiac images of clinical interest. |
Year | Venue | Keywords |
|---|---|---|
2006 | EUSIPCO | gaussian distribution,biological tissues,echocardiography,image segmentation,maximum likelihood estimation,medical image processing,probability,radiofrequency imaging,statistical analysis,pdf,rf signal,echocardiographic rf images,echocardiographic image segmentation,generalized gaussian distribution,maximum likelihood framework,probability density function,radio-frequency signal,statistical modelling,tissue segmentation,ultrasound cardiac images,ultrasound image segmentation |
DocType | ISSN | Citations |
Conference | 2219-5491 | 3 |
PageRank | References | Authors |
0.57 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Olivier Bernard | 1 | 9 | 2.14 |
| Jan D'hooge | 2 | 284 | 32.31 |
| Denis Friboulet | 3 | 403 | 32.65 |