C. Monserrat

Real-time deformable models for surgery simulation: a survey

Simulating the behaviour of elastic objects in real time is one of the current objectives of computer graphics. One of its fields of application lies in virtual reality, mainly in surgery simulation systems. In computer graphics, the models used for the construction of objects with deformable behaviour are known as deformable models. These have two conflicting characteristics: interactivity and motion realism. The different deformable models developed to date have promoted only one of these (usually interactivity) to the detriment of the other (biomechanical realism). In this paper, we present a classification of the different deformable models that have been developed. We present the advantages and disadvantages of each one. Finally, we make a comparison of deformable models and perform an evaluation of the state of the art and the future of deformable models.

Using augmented reality to treat phobias

Virtual reality (VR) is useful for treating several psychological problems, including phobias such as fear of flying, agoraphobia, claustrophobia, and phobia to insects and small animals. We believe that augmented reality (AR) could also be used to treat some psychological disorders. AR and VR share some advantages over traditional treatments. However, AR gives a greater feeling of presence (the sensation of being there) and reality judgment (judging an experience as real) than VR because the environment and the elements the patient uses to interact with the application are real. Moreover, in AR users see their own hands, feet, and so on, whereas VR only simulates this experience. With these differences in mind, the question arises as to the kinds of psychological treatments AR and VR are most suited for. In our system, patients see their own hands, feet, and so on. They can touch the table that animals are crossing or seeing their feet while the animals are running on the floor. They can also hold a marker with a dead spider or cockroach or pick up a flyswatter, a can of insecticide, or a dustpan.

An Advanced System for the Simulation and Planning of Orthodontic Treatments

This paper describes a new method for 3D orthodontic treatment simulation developed for an orthodontic planning system (MAGA-LLANES). We develop an original system for three-dimensional reconstruction of dental anatomy. Data are acquired directly from the patient with low cost 3D digitizers avoiding use of dental casts in orthodontic treatments. We apply these 3D dental models to simulate three-dimensional movement of teeth, including rotations, during orthodontic treatment. We develop an original simplified model of arch-wire behavior and a viscoplastic behavior law for the alveolar bone, to simulate teeth displacements during orthodontic treatments. The proposed algorithm enables to quantify the effect of orthodontic appliances on teeth movement. Preliminary results are very promising.

A new approach for the real-time simulation of tissue deformations in surgery simulation

Simulation of the behaviour of elastic objects in real time is one of the present objectives of computer graphics. One of its fields of application lies in virtual reality, mainly in surgery simulation systems. Models used for the construction of objects with deformable behaviour in computer graphics are known as deformable models. These have two conflicting characteristics: interactivity and movement realism. The deformable models developed up till now have promoted one characteristic to the detriment of the other. In this paper, a new approach is proposed based on boundary element methods (BEM). This is characterised by a positive equilibrium between speed and realism and great robustness. These properties along with the experimental results described in this paper permit one to assert that establishing deformable models with BEM is a reliable method to model objects in virtual reality environments for surgery simulation. In addition to that, the required elasticity parameters could be obtained experimentally through the use of a pigs liver.

Outlining of the prostate using snakes with shape restrictions based on the wavelet transform (Doctoral Thesis: Dissertation)

This paper considers the problem of deformable contour initialization and modeling for segmentation of the human prostate in medical images. We propose a new technique for elastic deformation restriction to particular object shapes of any closed planar curve using localized multiscale contour parameterization based on the 1D dyadic wavelet transform. For this purpose we define internal curve deformation forces as a result of multiscale parametrical contour analysis. The form restricted contour deformation and its initialization by template matching are performed in a coarse to fine segmentation process based on a multiscale image edge representation containing the important edges of the image at various scales. The method is useful for 3D conformal radiotherapy planning and automatic prostate volume measurements in ultrasonographic diagnosis.

Automatic Localization of Cephalometric Landmarks

A system for automatic detection of cephalometric landmarks is presented. Landmark detection is carried out in two steps: a line detection module searches for significant, well-contrasted lines of the image, such as the jaw line or the nasal spine. The landmark detection module uses the lines located in the first module to determine the search areas and then applies a pattern detection algorithm, based on mathematical morphology techniques. Relations between landmarks and lines are determined by means of a training process. The system has been tested for the detection of 17 landmarks on 20 images: more than 90% of the landmarks are accurately identified.

Contact model, fit process and, foot animation for the virtual simulator of the footwear comfort

This paper describes the new advances carried out for Simucal. Simucal was introduced in [13] and it is a footwear virtual simulator designed to perform studies of comfort and functionality in CAD footwear design. In this paper, a new finite element model for the deformation of shoe upper materials in gait is presented. This model provides a physical interpretation from the point of view of the contact mechanics to the previous model used in Simucal, as well as the new form of the problem allows that new materials and models can be easily computed. This paper also presents a wider description of the simulator, specifying the main tasks of the two main programs included in Simucal such as the initial fit performed by the Aligner. Finally, the process carried out to obtain the feet animation database is described.

Estimation of the elastic parameters of human liver biomechanical models by means of medical images and evolutionary computation

This paper presents a method to computationally estimate the elastic parameters of two biomechanical models proposed for the human liver. The method is aimed at avoiding the invasive measurement of its mechanical response. The chosen models are a second order Mooney-Rivlin model and an Ogden model. A novel error function, the geometric similarity function (GSF), is formulated using similarity coefficients widely applied in the field of medical imaging (Jaccard coefficient and Hausdorff coefficient). This function is used to compare two 3D images. One of them corresponds to a reference deformation carried out over a finite element (FE) mesh of a human liver from a computer tomography image, whilst the other one corresponds to the FE simulation of that deformation in which variations in the values of the model parameters are introduced. Several search strategies, based on GSF as cost function, are developed to accurately find the elastics parameters of the models, namely: two evolutionary algorithms (scatter search and genetic algorithm) and an iterative local optimization. The results show that GSF is a very appropriate function to estimate the elastic parameters of the biomechanical models since the mean of the relative mean absolute errors committed by the three algorithms is lower than 4%.

A new methodology for the in vivo estimation of the elastic constants that characterize the patient-specific biomechanical behavior of the human cornea

This work presents a methodology for the in vivo characterization of the complete biomechanical behavior of the human cornea of each patient. Specifically, the elastic constants of a hyperelastic, second-order Ogden model were estimated for 24 corneas corresponding to 12 patients. The finite element method was applied to simulate the deformation of human corneas due to non-contact tonometry, and an iterative search controlled by a genetic heuristic was used to estimate the elastic parameters that most closely approximates the simulated deformation to the real one. The results from a synthetic experiment showed that these parameters can be estimated with an error of about 5%. The results of 24 in vivo corneas showed an overlap of about 90% between simulation and real deformed cornea and a modified Hausdorff distance of 25 μm, which indicates the great accuracy of the proposed methodology.

Multiresolution segmentation of medical images using shape-restricted snakes

We propose a new technique for elastic deformation restriction of active contour models to particular object shapes. For this purpose we apply localized multi-scale contour parametrization based on the 1D dyadic Wavelet Transform (WT) as a multi-scale boundary curve analysis tool. Our approach determines the WT-coefficients within a certain scale range, which differ significantly from the correspondent WT-coefficients of the most similar model in a training set. Those WT-coefficients are replaced by the correspondent model WT-coefficients to perform the reconstruction of the contour. The difference of the original deformed contour and the reconstructed contour is used as inner snake forces. By this technique it can be avoided, that the deformable contour is trapped into disturbing local minima of the snakes potential due to noise or irrelevant image features. The contour deformation method is integrated in a coarse to fine segmentation frame based on a multiscale image edge representation using the local modulus maxima of the dyadic Wavelet Transform. For detection of the objects position and initialization of the snake we apply a multiresolution binary matched filter at a coarse scale containing few detail information.