Data-driven weight optimization for real-time mesh deformation

3D model deformation has been an active research topic in geometric processing. Due to its efficiency, linear blend skinning (LBS) and its follow-up methods are widely used in practical applications as an efficient method for deforming vector images, geometric models and animated characters. LBS needs to determine the control handles and specify their influence weights, which requires expertise and is time-consuming. Further studies have proposed a method for efficiently calculating bounded biharmonic weights of given control handles which reduces user effort and produces smooth deformation results. The algorithm defines a high-order shape-aware smoothness function which tends to produce smooth deformation results, but fails to generate locally rigid deformations. To address this, we propose a novel data-driven approach to producing improved weights for handles that makes full use of available 3D model data by optimizing an energy consisting of data-driven, rigidity and sparsity terms, while maintaining its advantage of allowing handles of various forms. We further devise an efficient iterative optimization scheme. Through contrast experiments, it clearly shows that linear blend skinning based on our optimized weights better reflects the deformation characteristics of the model, leading to more accurate deformation results, outperforming existing methods. The method also retains real-time performance even with a large number of deformation examples. Our ablation experiments also show that each energy term is essential

Design for metal fused filament fabrication (DfMF3) of Ti-6Al-4V alloy.

Additive manufacturing (AM) offers unmatchable freedom of design with the ability to manufacture parts from a wide range of materials. The technology of producing three-dimensional parts by adding material layer-by-layer has become relevant in several areas for numerous industries not only for building visual and functional prototypes but also for small and medium series production. Among others, while metal AM technologies have been established as production method, their adoption has been limited by expensive equipment, anisotropy in part properties and safety concerns related to working with loose reactive metal powder. To address this challenge, the dissertation aims at developing the fundamental understanding required to print metal parts with bound metal powder filaments using an extrusion-based AM process, known as metal fused filament fabrication (MF3). MF3 of Ti-6Al-4V has been investigated, owing to significant interest in the material from aerospace and medical industries on account of their high strength-to-weight ratio, excellent corrosion resistance and biocompatibility. To investigate the material-geometry-process interrelationship in MF3 printing, the current work looks into the process modeling and simulation, the influence of material composition and resulting characteristics on printed part properties, effects of printing parameters and slicing strategies on part quality, and part design considerations for printability. The outcome of the work is expected to provide the basis of design for MF3 (DfMF3) that is essential to unlocking the full potential of additive manufacturing. Moreover, the layer-by-layer extrusion-based printing with the highly filled material involves several challenges associated with printability, distortion and dimensional variations, residual stresses, porosity, and complexity in dealing with support structures. Currently, a high dependency on experimental trial-and-error methods to address these challenges limits the scope and efficiency of investigations. Hence, the current work presents a framework of design for MF3 and evaluates a thermo-mechanical model for finite element simulation of the MF3 printing process for virtual analyses. The capability to estimate these outcomes allows optimization of the material composition, part design, and process parameters before getting on to the physical process, reducing time and cost. The quantitative influence of material properties on MF3 printed part quality in terms of part deformation and dimensional variations was estimated using the simulation platform and results were corroborated by experiments. Also, a systematic procedure for sensitivity analysis has been presented that identified the most significant input parameters in MF3 from the material, geometry and process variables, and their relative influence on the print process outcome. Moreover, feasible geometry and process window were identified for supportless printing of Ti-6Al-4V lattice structures using the MF3 process, and an analytical approach has been presented to estimate the extrudate deflection at the unsupported overhangs in lattice structures. Finally, the design and fabrication of Ti-6Al-4V maxillofacial implants using MF3 technology are reported for the first time confirming the feasibility to manufacture patient-specific implants by MF3. The outcome of the work is an enhanced understanding of material-geometry-process interrelationships in MF3 governing DfMF3 that will enable effective design and manufacturing

Finite element modeling of soft tissue deformation.

Computer-aided minimally invasive surgery (MIS) has progressed significantly in the last decade and it has great potential in surgical planning and operations. To limit the damage to nearby healthy tissue, accurate modeling is required of the mechanical behavior of a target soft tissue subject to surgical manipulations. Therefore, the study of soft tissue deformations is important for computer-aided (MIS) in surgical planning and operation, or in developing surgical simulation tools or systems. The image acquisition facilities are also important for prediction accuracy. This dissertation addresses partial differential and integral equations (PDIE) based biomechanical modeling of soft tissue deformations incorporating the specific material properties to characterize the soft tissue responses for certain human interface behaviors. To achieve accurate simulation of real tissue deformations, several biomechanical finite element (FE) models are proposed to characterize liver tissue. The contribution of this work is in theoretical and practical aspects of tissue modeling. High resolution imaging techniques of Micro Computed Tomography (Micro-CT) and Cone Beam Computed Tomography (CBCT) imaging are first proposed to study soft tissue deformation in this dissertation. These high resolution imaging techniques can detect the tissue deformation details in the contact region between the tissue and the probe for small force loads which would be applied to a surgical probe used. Traditional imaging techniques in clinics can only achieve low image resolutions. Very small force loads seen in these procedures can only yield tissue deformation on the few millimeters to submillimeter scale. Small variations are hardly to detect. Furthermore, if a model is validated using high resolution images, it implies that the model is true in using the same model for low resolution imaging facilities. The reverse cannot be true since the small variations at the sub-millimeter level cannot be detected. In this dissertation, liver tissue deformations, surface morphological changes, and volume variations are explored and compared from simulations and experiments. The contributions of the dissertation are as follows. For liver tissue, for small force loads (5 grams to tens of grams), the linear elastic model and the neo-Hooke\u27s hyperelastic model are applied and shown to yield some discrepancies among them in simulations and discrepancies between simulations and experiments. The proposed finite element models are verified for liver tissue. A general FE modeling validation system is proposed to verify the applicability of FE models to the soft tissue deformation study. The validation of some FE models is performed visually and quantitatively in several ways in comparison with the actual experimental results. Comparisons among these models are also performed to show their advantages and disadvantages. The method or verification system can be applied for other soft tissues for the finite element analysis of the soft tissue deformation. For brain tissue, an elasticity based model was proposed previously employing local elasticity and Poisson\u27s ratio. It is validated by intraoperative images to show more accurate prediction of brain deformation than the linear elastic model. FE analysis of brain ventricle shape changes was also performed to capture the dynamic variation of the ventricles in author\u27s other works. There, for the safety reasons, the images for brain deformation modeling were from Magnetic Resonance Imaging (MRI) scanning which have been used for brain scanning. The measurement process of material properties involves the tissue desiccation, machine limits, human operation errors, and time factors. The acquired material parameters from measurement devices may have some difference from the tissue used in real state of experiments. Therefore, an experimental and simulation based method to inversely evaluate the material parameters is proposed and compare

Soft tissue modelling and facial movement simulation using the finite element method

This thesis presents a framework for soft tissue modelling, facial surgery simulation, and facial movement synthesis based on the volumetric finite element method. Assessment of facial appearance pre- and post-surgery is of major concern for both patients and clinicians. Pre-surgical planning is a prerequisite for successful surgical procedures and outcomes. Early computer-assisted facial models have been geometrically based. They are computationally efficient, but cannot give an accurate prediction for facial surgery simulation. Therefore, in this thesis, the emphasis is placed on physically-based methods, especially the finite element technique. To achieve realistic surgery simulation, soft tissue modelling is of crucial importance. Thus, in this thesis, considerable effort has been directed to develop constitutive equations for facial skeletal muscles. The skeletal muscle model subsequently developed is able to capture the complex mechanical properties of skeletal muscle, which are active, quasi-incompressible, fibre-reinforced and hyperelastic. In addition, to improve the characterisation of in-vivo muscle behaviour, a technique has been developed to visualise the internal fibre arrangement of skeletal muscle using the FEM-NURBS method, which is the combination of the finite element method and the non-uniform rational B-spline solid mathematical representation. Another principal contribution made in this thesis is the three-dimensional finite element facial model, which can be used for the simulations of facial surgery and facial movement. The procedure of one cranio-facial surgery is simulated by using this facial model and the numerical predictions show a good agreement with the patient post-surgical data. In addition, it would be very helpful to also simulate the facial movement and facial expressions. In this thesis, two facial expressions (smile and disgust) and the mouth opening are simulated to assess the post-surgical appearance and test the muscle-driven facial movement simulation method

Physically Based Forehead Modelling and Animation including Wrinkles

There has been a vast amount of research on the production of realistic facial models and animations, which is one of the most challenging areas of computer graphics. Recently, there has been an increased interest in the use of physically based approaches for facial animation, whereby the effects of muscle contractions are propagated through facial soft-tissue models to automatically deform them in a more realistic and anatomically accurate manner. Presented in this thesis is a fully physically based approach for efficiently producing realistic-looking animations of facial movement, including animation of expressive wrinkles, focussing on the forehead. This is done by modelling more physics-based behaviour than current computer graphics approaches. The presented research has two major components. The first is a novel model creation process to automatically create animatable non-conforming hexahedral finite element (FE) simulation models of facial soft tissue from any surface mesh that contains hole-free volumes. The generated multi-layered voxel-based models are immediately ready for simulation, with skin layers and element material properties, muscle properties, and boundary conditions being automatically computed. The second major component is an advanced optimised GPU-based process to simulate and visualise these models over time using the total Lagrangian explicit dynamic (TLED) formulation of the FE method. An anatomical muscle contraction model computes active and transversely isotropic passive muscle stresses, while advanced boundary conditions enable the sliding effect between the superficial and deep soft-tissue layers to be simulated. Soft-tissue models and animations with varying complexity are presented, from a simple soft-tissue-block model with uniform layers of skin and muscle, to a complex forehead model. These demonstrate the flexibility of the animation approach to produce detailed animations of realistic gross- and fine-scale soft-tissue movement, including wrinkles, with different muscle structures and material parameters, for example, to animate different-aged skin. Owing to the detail and accuracy of the models and simulations, the animation approach could also be used for applications outside of computer graphics, such as surgical applications. Furthermore, the animation approach can be used to animate any multi-layered soft body (not just soft tissue)

Variational methods for modeling and simulation of tool-tissue interaction

Ph.DDOCTOR OF PHILOSOPH

Effect of Orthognathic Surgery on the Upper Airway System

Sleep apnea is a disease which has not been getting an adequate amount of attention in the research community for a long time. However, the strain on the cardiovascular system and other serious problems, such as daytime sleepiness and even neurocognitive dysfunction, that it causes may be severe in advanced cases of the illness, as such it can significantly affect the heart especially and lead to cardiac arrest. Thus, it has been receiving a lot of attention recently. Tampere University Hospital has a goal of creating a comprehensive upper airway airflow model for surgery outcome prediction. That requires knowledge of available models and analysis of static magnetic resonance images, among other things. This document deals with these two main issues. This thesis has two major parts, one of them being a literature review of sleep apnea and models used in airflow modelling in the upper airways. Modelling of airflow generally includes acquisition of a static upper airway system model (in the case of upper airway modelling) and then adding a dynamic component to it. The second part of this thesis deals with acquisition of the static model, which involves segmentation of MRI image sets from 3 patients (pre- and post-operative sequences). It also answers the question, whether the effect of orhtognathic surgery on the upper airway system can be seen from volumetric analysis of the segmented images and the segmented images themselves. The main methods of adding a dynamic component to the static model turned out to be computational fluid mechanics and finite element modelling, including their sub-methods, such as direct numerical simulation of large eddy simulation. As with the second part of the thesis, the volumetric segmentation data is rather inconclusive and should not be related solely for evaluation of the effect of orthognathic surgery on the upper airway system. It can be said, nonetheless, that the volume of the upper airway itself is rather easily obtainable and reliable. The images themselves, however, provide very visual information about that, and shifting of certain muscles and muscle groups and other structures can be seen

Development and Validation Methodology of the Nuss Procedure Surgical Planner

Pectus excavatum (PE) is a congenital chest wall deformity which is characterized, in most cases, by a deep depression of the sternum. A minimally invasive technique for the repair of PE (MIRPE), often referred to as the Nuss procedure, has been proven to be more advantageous than many other PE treatment techniques. The Nuss procedure consists of placement of a metal bar(s) underneath the sternum, thereby forcibly changing the geometry of the ribcage. Because of the prevalence of PE and the popularity of the Nuss procedure, the demand to perform this surgery is greater than ever. Therefore, a Nuss procedure surgical planner would be an invaluable planning tool ensuring an optimal physiological and aesthetic outcome. In this dissertation, the development and validation of the Nuss procedure planner is investigated. First, a generic model of the ribcage is developed to overcome the issue of missing cartilage when PE ribcages are segmented and facilitate the flexibility of the model to accommodate a range of deformity. Then, the CT data collected from actual patients with PE is used to create a set of patient specific finite element models. Based on finite element analyses performed over those models, a set force-displacement data set is created. This data is used to train an artificial neural network to generalize the data set. In order to evaluate the planning process, a methodology which uses an average shape of the chest for comparison with results of the Nuss procedure planner is developed. This method is based on a sample of normal chests obtained from the ODU male population using laser surface scanning and overcomes challenging issues such as hole-filling, scan registration and consistency. Additionally, this planning simulator is optimized so that it can be used for training purposes. Haptic feedback and inertial tracking is implemented, and the force-displacement model is approximated using a neural network approach and evaluated for real-time performance. The results show that it is possible to utilize this approximation of the force-displacement model for the Nuss procedure simulator. The detailed ribcage model achieves real-time performance