Multimodality cardiovascular image segmentation using a deformable contour model

Comput Med Imaging Graph. 1997 Mar-Apr;21(2):79-89. doi: 10.1016/s0895-6111(96)00070-5.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Blood
  • Blood Vessels / anatomy & histology
  • Cardiovascular System / anatomy & histology*
  • Cineradiography
  • Diagnostic Imaging*
  • Echocardiography
  • Heart / anatomy & histology
  • Humans
  • Image Enhancement / methods*
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging
  • Magnetic Resonance Imaging, Cine
  • Models, Cardiovascular*
  • Radiographic Image Enhancement
  • Tomography, X-Ray Computed
  • Ultrasonography, Interventional