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Title: Autoregressive modeling application for vascular zones detection in the contrast echographic images
Authors: Ghazal, Bilal
Khachab, Maha 
Cachard, Christian
Friboulet, Denis
Mokbel, Chafic 
Affiliations: Faculty of Medicine 
Department of Electrical Engineering 
Keywords: Medical image processing
Autoregressive processes
Biomedical ultrasonics
Image classification
Image enhancement
Subjects: Blood-vessels
Image segmentation
Issue Date: 2007
Publisher: IEEE
Part of: 9th International Symposium on Signal Processing and Its Applications, 2007. ISSPA 2007.
Start page: 1
End page: 4
Conference: International Symposium on Signal Processing and Its Applications (9th : 12-15 Feb. 2007 : Sharjah, United Arab Emirates) 
Contrast agents are used in ultrasound imaging to enhance blood region and thereby separate the perfused area and the surrounding tissues. But unfortunately the signals backscattered from agent and tissues are still close. So it is necessary to implement signal processing to enhance the contrast echo. In this article, we apply the autoregressive model to exploit the nonlinear behavior agent properties. Then, we process the obtained pictures by a classification method followed by erosion dilatation algorithm to obtain a satisfying differentiation of the ultrasound image into two classes. The Agent to Tissue Ratio (ATR) factor is used to compare the performance of the methods, and the Fisher criterion is used to study the classification feasibility.
Open URL: Link to full text
Type: Conference Paper
Appears in Collections:Faculty of Medicine

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