Statistical atlas-based sub-voxel segmentation of 3D brain MRI

We present a 3D brain MRI segmentation method in which a high resolution label image evolves under the influence of multiple constraints. The constraints are expressed in a versatile energy minimization framework which allows for evolutions only at label boundaries, effectively making it a surface evolution system. Constraints are defined using atlas-mapped parameters. The atlas, composed of a reference image and parameter values, is mapped onto the source image using a multi-resolution deformable image matching method. Variable scale image constraints are considered. The prior model currently includes: a relative distribution constraint, which gives the probability of observing a label at a given distance from another label, a thickness constraint and a surface regularization constraint. Issues related to partial volumes are addressed by the use of a high resolution label image and an accurate model of the acquisition process. High resolution segmentations are thus obtained from stan...

• Type: Conference
• Year: 2003
• Where: ICIP
• Authors: Marcel Bosc, Fabrice Heitz, Jean-Paul Armspach
• Keywords: ICIP 2003, Image Processing, Multi-resolution Deformable Image, Relative Distribution Constraint, Resolution Label Image, Scale Image Constraints, Surface Regularization Constraint