Ultrasound Backscatter characterization by using Markov random field model

Nizar Bouhlel (1) , Sylvie Sevestre-Ghalila (1) , Mériem Jaidane (2) , Christine Graffigne (1)

1 MAP5 - UMR 8145 - Mathématiques Appliquées Paris 5
2 U2S - Unité signaux et systèmes

This paper evaluates a K-Markov random field model for retrieving information about backscatter characteristics, especially regularity spacing scatterers in simulated ultrasound image. The model combines a statistical K-distribution that describes the envelope of backscattered echo and spatial interaction given by Markov random field (MRF). Parameters estimated by the conditional least squares (CLS) estimation method on simulated radio-frequency (RF) envelope image show that the interaction parameters measure the degree of the randomness of the scatterers.

Mots clés: Tissue Characterization; Ultrasound RF image; Texture; Markov Model; K-Distribution; Tissue Characterization.

Domaines: Traitement du signal et de l'image [eess.SP]; Probabilités [math.PR]; Traitement du signal et de l'image [eess.SP]

Nizar Bouhlel, Sylvie Sevestre-Ghalila, Mériem Jaidane, Christine Graffigne. Ultrasound Backscatter characterization by using Markov random field model. IEEE International Conference on Acoustics, Speech and Signal Processing, May 2006, Toulouse, France. pp.1124-1127. ⟨hal-00173925⟩