Implicit active contours for ultrasound images segmentation driven by phase information and local maximum likelihood

Ahror Belaid (1) , Djamal Boukerroui (1) , Yves Maingourd (2) , Jean-Françoise Lerallut (1)

1 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]
2 CHU Amiens-Picardie

This paper presents a new method in a variational level set framework for ultrasound images segmentation. The conventional intensity gradient based methods have had limited success on ultrasound images. Phase based methods, which are theoretically intensity-invariant, offer a good alternative. The proposed approach uses a speed term based on local phase derived from the monogenic signal. In order to confront more the speckle noise and local changes of intensity, the proposed phase based geodesic active contours term is combined with a new local maximum likelihood region term. A Rayleigh probability distribution is considered to model the B-mode ultrasound images intensities. Preliminary results show that the proposed model is robust to attenuation and captures well the low contrast boundaries.

Mots clés: Maximum likelihood; Echocardiography; Level set segmentation; Local phase; Monogenic signal

Domaines: Imagerie médicale

Ahror Belaid, Djamal Boukerroui, Yves Maingourd, Jean-Françoise Lerallut. Implicit active contours for ultrasound images segmentation driven by phase information and local maximum likelihood. 8th International Symposium on Biomedical Imaging (ISBI'11), Mar 2011, Chicago, Illinois, France. pp.630-635. ⟨hal-00586401⟩