Tracking the interframe deformation of structures in 3D ultrasound imaging

Three dimensional ultrasound imaging with a freehand probe allows a flexible approach to medical visualization and diagnosis. Given the imperfect accuracy of proprioceptive devices used to log the position and tilt of the probe, it is important to utilize the position constraints provided by image evidence. This is also important if we wish to consider the visualization of structures which move significantly during acquisition, such as a heart of fetus. We present here an initial approach to more robust segmentation and shape recovery in a particularly noisy modality. We consider 2D segmentation based on edge evidence, using first an active contour, then finding an optimal segmentation using simulated annealing. Correspondence between contours in adjacent frames can only be solved in general cases by use of a 3D prior model. Dynamic physics-based mesh models as used by Pentland [20] and Nastar [17], allow for shape modelling, then over-constrained 3D shape recovery can be performed using the intrinsic vibration modes of the model.

[1]  Chin-Tu Chen,et al.  Automatic left ventricular boundary detection in digital two-dimensional echocardiography using fuzzy reasoning techniques , 1990, Other Conferences.

[2]  Ren C. Luo,et al.  Surface reconstruction based on descriptions of cross-sectional contours , 1990, Other Conferences.

[3]  Nicholas Ayache,et al.  Non-Rigid Motion Analysis in Medical Images: a Physically Based Approach , 1993, IPMI.

[4]  D.E. Thompson,et al.  Construction of biological surface models from cross-sections image processing , 1993, IEEE Transactions on Biomedical Engineering.

[5]  Alex Pentland,et al.  Closed-form solutions for physically-based shape modeling and recognition , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Laurent D. Cohen,et al.  Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  S. Y. Chen,et al.  Improvement on dynamic elastic interpolation technique for reconstructing 3-D objects from serial cross sections [biomedical application]. , 1990, IEEE transactions on medical imaging.

[8]  Alex Pentland,et al.  Recovery of Nonrigid Motion and Structure , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Donald Geman,et al.  Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images , 1984 .

[10]  Stephen M. Pizer,et al.  Edge-Affected Context for Adaptive Contrast Enhancement , 1991, IPMI.

[11]  Jean-Daniel Boissonnat,et al.  Three-dimensional reconstruction of complex shapes based on the Delaunay triangulation , 1993, Electronic Imaging.