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PubMed · 9152573

Multimodality cardiovascular image segmentation using a deformable contour model.

A Sebbahi·A Herment·A de Cesare·Mousseaux
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Abstract

An automatic segmentation method has been developed for cardiovascular multimodality imaging. A "snake" model based on a curve shaping and an energy-minimizing process is used to detect blood-wall interfaces on Cine-CT, MRI and ultrasound images. Deformation of a reduced set of contour points was made according to a discretized global, regional and local minimum energy criterion. A continuous regional optimization process was also integrated into the deformation model, it takes into account a cubic spline interpolation and adaptive regularity constraints. The constraints provided rapid convergence toward a final contour position by successively stopping spline segments.

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AlgorithmsBloodBlood VesselsCardiovascular SystemCineradiographyDiagnostic ImagingEchocardiographyHeartHumansImage EnhancementImage Processing, Computer-AssistedMagnetic Resonance ImagingMagnetic Resonance Imaging, CineModels, CardiovascularRadiographic Image EnhancementTomography, X-Ray ComputedUltrasonography, InterventionalJournal ArticleResearch Support, Non-U.S. Gov't

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A Sebbahi, A Herment, A de Cesare, Mousseaux. Multimodality cardiovascular image segmentation using a deformable contour model.. https://doi.org/10.1016/s0895-6111(96)00070-5

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