An introduction to splines for use in computer graphics & geometric modeling
An introduction to splines for use in computer graphics & geometric modeling
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Computer and Robot Vision
Surface Representation with Deformable Splines: Using Decoupled Variables
IEEE Computational Science & Engineering
Snakes and Splines for Tracking Non-Rigid Heart Motion
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
A snake for model-based segmentation
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
A multiresolution method for tagline detection and indexing
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
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To date, MRI-SPAMM data from different image slices have been analyzed independently. In this paper, we propose an approach for 3D tag localization and tracking of SPAMM data by a novel deformable B-solid. The solid is defined in terms of a 3D tensor product B-spline. The isoparametric curves of the B-spline solid have special importance. These are termed implicit snakes as they deform under image forces from tag lines in different image slices. The localization and tracking of tag lines is peiformed under constraints of continuity and smoothness of the B-solid. The framework unifies the problems of localization, and displacement fitting and interpolation into the same procedure utilizing B-spline bases for interpolation. To track motion from boundaries and restrict image forces to the myocardium, a volumetric model is employed as a pair of coupled endocardial and epicardial B-spline suifaces. To recover deformations in the LV an energy-minimization problem is posed where both tag and LV boundary data are used. The framework has been implemented on tag data from Short Axis (SA) cardiac images, as well as SA left ventricle (LV) boundaries, and is currently being extended to include Long Axis (LA) data.