Title :
Tissue Identification in Ultrasound Images using Rayleigh Local Parameter Estimation
Author :
Aja-Fernandez, Santiago ; Martin-Fernandez, Marcos ; Alberola-López, Carlos
Author_Institution :
Univ. de Valladolid, Valladolid
Abstract :
A method to identify different tissues in ultrasound images is presented. Assuming a Rayleigh model for speckle, the different tissues present in the image will be related to the Rayleigh sigma parameter, with different values for each different tissue. The parameter is locally estimated using well known estimation methods for the Rayleigh distribution, such as the maximum likelihood estimator. A significant increase in the separability of the different tissues present in the image is then achieved. A subsequent clustering process based on the position of the maxima of the estimator distribution allows the classification of each pixel in a tissue class.
Keywords :
biological tissues; biomedical ultrasonics; maximum likelihood estimation; medical image processing; speckle; Rayleigh distribution; Rayleigh local parameter estimation; clustering; maximum likelihood estimator; speckle; tissues; ultrasound images; Dynamic range; Image coding; Maximum likelihood detection; Maximum likelihood estimation; Parameter estimation; Radar scattering; Rayleigh scattering; Speckle; Telecommunication standards; Ultrasonic imaging;
Conference_Titel :
Bioinformatics and Bioengineering, 2007. BIBE 2007. Proceedings of the 7th IEEE International Conference on
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-1509-0
DOI :
10.1109/BIBE.2007.4375702