Efficient techniques for soft tissue modeling and simulation

Performing realistic deformation simulations in real time is a challenging problem in computer graphics. Among numerous proposed methods including Finite Element Modeling and ChainMail, we have implemented a mass spring system because of its acceptable accuracy and speed. Mass spring systems have, however, some drawbacks such as, the determination of simulation coefficients with their iterative nature. Given the correct parameters, mass spring systems can accurately simulate tissue deformations but choosing parameters that capture nonlinear deformation behavior is extremely difficult. Since most of the applications require a large number of elements i. e. points and springs in the modeling process it is extremely difficult to reach realtime performance with an iterative method. We have developed a new parameter identification method based on neural networks. The structure of the mass spring system is modified and neural networks are integrated into this structure. The input space consists of changes in spring lengths and velocities while a "teacher" signal is chosen as the total spring force, which is expressed in terms of positional changes and applied external forces. Neural networks are trained to learn nonlinear tissue characteristics represented by spring stiffness and damping in the mass spring algorithm. The learning algorithm is further enhanced by an adaptive learning rate, developed particularly for mass spring systems. In order to avoid the iterative approach in deformation simulations we have developed a new deformation algorithm. This algorithm defines the relationships between points and springs and specifies a set of rules on spring movements and deformations. These rules result in a deformation surface, which is called the search space. The deformation algorithm then finds the deformed points and springs in the search space with the help of the defined rules. The algorithm also sets rules on each element i. e. triangle or tetrahedron so that they do not pass through each other. The new algorithm is considerably faster than the original mass spring systems algorithm and provides an opportunity for various deformation applications. We have used mass spring systems and the developed method in the simulation of craniofacial surgery. For this purpose, a patient-specific head model was generated from MRI medical data by applying medical image processing tools such as, filtering, the segmentation and polygonal representation of such model is obtained using a surface generation algorithm. Prism volume elements are generated between the skin and bone surfaces so that different tissue layers are included to the head model. Both methods produce plausible results verified by surgeons.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Determination of critical factors for fast and accurate 2D medical image deformation

The advent of medical imaging technology enabled physicians to study patient anatomy non-invasively and revolutionized the medical community. As medical images have become digitized and the resolution of these images has increased, software has been developed to allow physicians to explore their patients\u27 image studies in an increasing number of ways by allowing viewing and exploration of reconstructed three-dimensional models. Although this has been a boon to radiologists, who specialize in interpreting medical images, few software packages exist that provide fast and intuitive interaction for other physicians. In addition, although the users of these applications can view their patient data at the time the scan was taken, the placement of the tissues during a surgical intervention is often different due to the position of the patient and methods used to provide a better view of the surgical field. None of the commonly available medical image packages allow users to predict the deformation of the patient\u27s tissues under those surgical conditions. This thesis analyzes the performance and accuracy of a less computationally intensive yet physically-based deformation algorithm- the extended ChainMail algorithm. The proposed method allows users to load DICOM images from medical image studies, interactively classify the tissues in those images according to their properties under deformation, deform the tissues in two dimensions, and visualize the result. The method was evaluated using data provided by the Truth Cube experiment, where a phantom made of material with properties similar to liver under deformation was placed under varying amounts of uniaxial strain. CT scans were before and after the deformations. The deformation was performed on a single DICOM image from the study that had been manually classified as well as on data sets generated from that original image. These generated data sets were ideally segmented versions of the phantom images that had been scaled to varying fidelities in order to evaluate the effect of image size on the algorithm\u27s accuracy and execution time. Two variations of the extended ChainMail algorithm parameters were also implemented for each of the generated data sets in order to examine the effect of the parameters. The resultant deformations were compared with the actual deformations as determined by the Truth Cube experimenters. For both variations of the algorithm parameters, the predicted deformations at 5% uniaxial strain had an RMS error of a similar order of magnitude to the errors in a finite element analysis performed by the truth cube experimenters for the deformations at 18.25% strain. The average error was able to be reduced by approximately between 10-20% for the lower fidelity data sets through the use of one of the parameter schemes, although the benefit decreased as the image size increased. When the algorithm was evaluated under 18.25% strain, the average errors were more than 8 y times that of the errors in the finite element analysis. Qualitative analysis of the deformed images indicated differing degrees of accuracy across the ideal image set, with the largest displacements estimated closer to the initial point of deformation. This is hypothesized to be a result of the order in which deformation was processed for points in the image. The algorithm execution time was examined for the varying generated image fidelities. For a generated image that was approximately 18.5% of the size of the tissue in the original image, the execution time was less than 15 seconds. In comparison, the algorithm processing time for the full-scale image was over 3 y hours. The analysis of the extended ChainMail algorithm for use in medical image deformation emphasizes the importance of the choice of algorithm parameters on the accuracy of the deformations and of data set size on the processing time

Development of a Computational Model to Predict the In Vivo Contact Mechanics of Modern Total Knee Arthroplasty

This dissertation focuses on the development of a computationally efficient and fast method that incorporates the kinematics obtained from fluoroscopy and extends it to the prediction of the in-vivo contact mechanics at the femoro-tibial articulation in modern knee implants for the deep knee bend activity. In this endeavor, this dissertation deals with the use of an inverse dynamic rigid body model characterizing the slip and roll behavior observed in the femoro-polyethylene articulation and a coupled deformation model where the polyethylene in knee implants are modeled as hexahedral discrete element networks. The performance of this method is tested by comparing force predictions from a telemetric knee and finite element analysis. Finally, the method is applied to study the in vivo contact mechanics and mechanics of the quadriceps mechanism in six popular knee designs. During the deep knee bend activity, the contact force generally increased with flexion. However, the medial lateral forces were not equally distributed and the medial lateral force distribution generally varied from 60%- 40% at full extension to as high as 75%-25% at full flexion in some patients. Also, the magnitude of axial force in the superior-inferior direction was the highest and was found to contribute around 98%-99% of the total load acting at the femorotibial joint. The forces in the medio-lateral and antero-posterior directions were low and the maximum magnitude observed was around 0.5BW. The contact areas and contact pressures were much more sensitive to the geometries involved and the in vivo kinematics. Though no definite pattern was observed for the variation of the contact areas throughout flexion, the contact pressures increased in both condyles with increasing flexion. Also, the contact pressures on the medial condyle were higher than the contact pressures observed in the lateral condyle. The patellofemoral and the quadriceps force ratio increased with the increase in flexion while the patellar ligament and the quadriceps force ratio decreased with increasing flexion. In some patients at high flexion, the quadriceps force and as a result the patellofemoral, patellar ligament and the knee contact forces were found to decrease due to the wrapping of the quadriceps coupled with posterior movement of the femoral condyles leading to the increase in the quadriceps moment arm

Vector offset operators for deformable organic objects.

Many natural materials and most of living tissues exhibit complex deformable behaviours that may be characteriseda s organic. In computer animation, deformable organic material behaviour is needed for the development of characters and scenes based on living creatures and natural phenomena. This study addresses the problem of deformable organic material behaviour in computer animated objects. The focus of this study is concentrated on problems inherent in geometry based deformation techniques, such as non-intuitive interaction and difficulty in achieving realism. Further, the focus is concentrated on problems inherent in physically based deformation techniques, such as inefficiency and difficulty in enforcing spatial and temporal constraints. The main objective in this study is to find a general and efficient solution to interaction and animation of deformable 3D objects with natural organic material properties and constrainable behaviour. The solution must provide an interaction and animation framework suitable for the creation of animated deformable characters. An implementation of physical organic material properties such as plasticity, elasticity and iscoelasticity can provide the basis for an organic deformation model. An efficient approach to stress and strain control is introduced with a deformation tool named Vector Offset Operator. Stress / strain graphs control the elastoplastic behaviour of the model. Strain creep, stress relaxation and hysteresis graphs control the viscoelastic behaviour of the model. External forces may be applied using motion paths equipped with momentum / time graphs. Finally, spatial and temporal constraints are applied directly on vector operators. The suggested generic deformation tool introduces an intermediate layer between user interaction, deformation, elastoplastic and viscoelastic material behaviour and spatial and temporal constraints. This results in an efficient approach to deformation, frees object representation from deformation, facilitates the application of constraints and enables further development

Virtual Hand Representations to Support Natural Interaction in Immersive Environment

Immersive Computing Technology (ICT) offers designers the unique ability to evaluate human interaction with product design concepts through the use of stereo viewing and 3D position tracking. These technologies provide designers with opportunities to create virtual simulations for numerous different applications. In order to support the immersive experience of a virtual simulation, it is necessary to employ interaction techniques that are appropriately mapped to specific tasks. Numerous methods for interacting in various virtual applications have been developed which use wands, game controllers, and haptic devices. However, if the intent of the simulation is to gather information on how a person would interact in an environment, more natural interaction paradigms are needed. The use of 3D hand models coupled with position-tracked gloves provide for intuitive interactions in virtual environments. This paper presents several methods of representing a virtual hand model in the virtual environment to support natural interaction