A probabilistic deformable model for the representation of brain structures is described. The statistically learned deformable model represents the relative location of head (skull and scalp) and brain surfaces in Magnetic Resonance Images (MRIs) and accommodates their significant variability across different individuals. The head and brain surfaces of each volume are parameterized by the ampli...

We present a method that allows both autonomous and human-robot collaborative manipulation of deformable objects. The method does not require modeling and simulating deformation. Our method is based on the concept of diminishing rigidity, which we use to quickly compute an approximation to the Jacobian of the deformable object without using simulation. This Jacobian is used to drive the points ...

Active contour and surface models, also known as deformable models, are powerful image segmentation techniques. Geometric deformable models implemented using level set methods have advantages over parametric models due to their intrinsic behavior, parameterization independence, and ease of implementation. However, a long claimed advantage of geometric deformable models — the ability to automati...

Using deformable models to register medical images can result in problems of initialization of deformable models and robustness and accuracy of matching of inter-subject anatomical variability. To tackle these problems, a novel model is proposed in this paper by compounding local invariant features and global deformable geometry. This model has four steps. First, a set of highly-repeatable and ...

To investigate the possibility of the enhancing effect of deformable vesicles on buccal delivery of insulin, two kinds of vesicles with and without the presence of sodium deoxycholate (deformable vesicles and conventional vesicles) were prepared by reverse phase evaporation methods. The liposomal entrapment efficiency was determined by column chromatography. The particle size and morphology of ...

Statistical models of deformations (SMD) capture the variability of deformations from the template image onto a group of sample images and can be used to constrain the traditional deformable registration algorithms to improve their robustness and accuracy. This paper employs a wavelet-PCA-based SMD to constrain the traditional deformable registration based on the Bayesian framework. The templat...

We have developed a new approach to shape-based tracking and analysis of cardiac MR images using geometrically deformable templates (GDTs). We propose to use an energyminimizing deformable template which can deform into similar shapes under the in uence of external forces. The degree of deformation of the template from its equilibrium shape is expressed by the amount of bending energy which is ...

Active contour and surface models, also known as deformable models, constitute a class of powerful segmentation techniques. Geometric deformable models implemented via level-set methods have advantages over parametric ones due to their intrinsic behavior, parameterization independence, and ease of implementation. However, a long claimed advantage of geometric deformable models — the ability to ...

Deformable models are used extensively in image processing, computer vision, and medical imaging applications, particularly to delineate object boundaries. Problems associated with initialization and poor convergence to boundary concavities, however, have limited their utility. This chapter presents an external force for deformable models, largely solving both problems. This external force, whi...

Ubiquity is a trend and vision of modern computer science. Planting physics-based deformable object simulation, which provides realism to animation and medical simulation, into ubiquitous computing environments will make a step forward to envisioned realism in the ubiquity of computation. The essential components of embedding physics-based deformable simulation to ubiquitous computational envir...