The aim of this paper is to propose a new Markov Random Field (MRF) for textured ultrasound image which use is more relevant than the use of the classic MRF, such as the gaussian markovian model. The main difference is that our model is based on κ-distribution. We have built this κ-MRF with reference to the Product Model. This latter means that the observed intensities of ultrasound image are the product of a degraded perfect image by a multiplicative noise called speckle. When the construct of κ-MRF is already described, we propose in this paper a validation on synthetic and medical B-scan textured image. The synthetic textures are obtained by stimulating the κ-MRF. For medical texture, we estimate the parameters of the model from tissues. The estimated parameters are simulated and compared to medical texture. The resemblance is a first validation of the κ-MRF and the tissue can be then characterized by the parameters of the model.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.