Automated thermal coagulation segmentation of three-dimensional elastographic imaging using an active contour model

Delineation of RF-ablator induced coagulation (thermal lesion) boundaries is an important clinical problem not well addressed by conventional imaging modalities. Automation of this process is certainly desirable. Elastography, that estimates and images the local strain corresponding to small, externally applied, quasi-static compressions, can be used for visualization of thermal coagulations. Several studies have demonstrated that coagulation volumes computed from multiple planar slices through the region of interest are more accurate than volumes estimated assuming simple shapes and incorporating single or orthogonal diameter estimates. The paper presents an automated segmentation approach for thermal coagulations on three-dimensional elastographic data to obtain both area and volume information. This approach consists of a coarse-to-fine method for active contour initialization and a gradient vector flow active contour model for deformable contour optimization with the help of prior knowledge of the geometry of general thermal coagulations. The performance of the proposed algorithm is shown to be comparable to manual delineation by medical physicists (r=0.99 for 36 RF-induced coagulations). The correlation coefficient of the coagulation volume between auto-segmented elastography and manually-delineated pathology is 0.96.