Reconstruction of 3D human facial images using partial differential equations.

One of the challenging problems in geometric modeling and computer graphics is the construction of realistic human facial geometry. Such geometry are essential for a wide range of applications, such as 3D face recognition, virtual reality applications, facial expression simulation and computer based plastic surgery application. This paper addresses a method for the construction of 3D geometry of human faces based on the use of Elliptic Partial Differential Equations (PDE). Here the geometry corresponding to a human face is treated as a set of surface patches, whereby each surface patch is represented using four boundary curves in the 3-space that formulate the appropriate boundary conditions for the chosen PDE. These boundary curves are extracted automatically using 3D data of human faces obtained using a 3D scanner. The solution of the PDE generates a continuous single surface patch describing the geometry of the original scanned data. In this study, through a number of experimental verifications we have shown the efficiency of the PDE based method for 3D facial surface reconstruction using scan data. In addition to this, we also show that our approach provides an efficient way of facial representation using a small set of parameters that could be utilized for efficient facial data storage and verification purposes

Automatic features characterization from 3d facial images.

This paper presents a novel and computationally fast method for automatic identification of symmetry profile from 3D facial images. The algorithm is based on the concepts of computational geometry which yield fast and accurate results. In order to detect the symmetry profile of a human face, the tip of the nose is identified first. Assuming that the symmetry plane passes through the tip of the nose, the symmetry profile is then extracted. This is undertaken by means of computing the intersection between the symmetry plane and the facial mesh, resulting in a planner curve that accurately represents the symmetry profile. Experimentation using two different 3D face databases was carried out, resulting in fast and accurate results

Physically-based forehead animation including wrinkles

Physically-based animation techniques enable more realistic and accurate animation to be created. We present a fully physically-based approach for efficiently producing realistic-looking animations of facial movement, including animation of expressive wrinkles. This involves simulation of detailed voxel-based models using a graphics processing unit-based total Lagrangian explicit dynamic finite element solver with an anatomical muscle contraction model, and advanced boundary conditions that can model the sliding of soft tissue over the skull. The flexibility of our approach enables detailed animations of gross and fine-scale soft-tissue movement to be easily produced with different muscle structures and material parameters, for example, to animate different aged skins. Although we focus on the forehead, our approach can be used to animate any multi-layered soft body

Comparison of linear and non-linear soft tissue models with postoperative ct scan in maxillofacial surgery

Abstract. A Finite Element model of the face soft tissue is proposed to simulate the morphological outcomes of maxillofacial surgery. Three modelling options are implemented: a linear elastic model with small and large deformation hypothesis, and an hyperelastic Mooney-Rivlin model. An evaluation procedure based on a qualitative and quantitative comparison of the simulations with a post-operative CT scan is detailed. It is then applied to one clinical case to evaluate the differences between the three models, and with the actual patient morphology. First results shows in particular that for a "simple" clinical procedure where stress is less than 20%, a linear model seams sufficient for a correct modelling

파티클 시뮬레이션을 이용한 물리 기반 비강체 정합 기술

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2013. 8. 신영길.Recent advances in computing hardware have enabled the application of physically based simulation techniques to various research fields for improved accuracy. In this paper, we present a novel physically based non-rigid registration method using smoothed particle hydrodynamics (SPH) for hepatic metastasis volume-preserving registration between follow-up liver CT images. Our method models the liver and hepatic metastasis as a set of particles carrying their own physical properties. Based on the fact that the hepatic metastasis is stiffer than other normal cells in the liver parenchyma, the candidate regions of hepatic metastasis are modeled with particles of higher stiffness compared to the liver parenchyma. Particles placed in the liver and candidate regions of hepatic metastasis in the source image are transformed along a gradient vector flow (GVF)-based force field calculated in the target image. In this transformation, the particles are physically interacted and deformed by a novel deformable particle method which is proposed to preserve the hepatic metastasis to the best. In experimental results using 10 clinical datasets, our method matches the liver effectively between follow-up CT images as well as preserves the volume of hepatic metastasis almost completely, enabling the accurate assessment of the volume change of the hepatic metastasis. These results demonstrated a potential of the proposed method that it can deliver a substantial aid in measuring the size change of index lesion (i.e., hepatic metastasis) after the chemotheraphy of metastasis patients in radiation oncology.최근 컴퓨팅 하드웨어의 발달은 정확도 향상을 위해 물리 기반의 시뮬레이션 기술을 다양한 연구 분야에 적용할 수 있게 하였다. 본 논문에서는 입자를 이용하여 시뮬레이션하는 방법 중 하나인 입자 보간 방식의 유체역학(smoothed particle hydrodynamics) 기술을 이용하여, 후속 컴퓨터 단층촬영 영상(computed tomography) 사이에 간전이(hepatic metastasis) 체적을 보전하는 물리 기반의 비정형체 정합 기술을 제안한다. 제안 방법은 간과 간전이를 물리적 속성을 동반하는 일련의 입자로 표현하며, 간전이가 정상 간에 비해 강한 탄성을 보인다는 사실에 기반하여 간전이로 짐작되는 부위를 상대적으로 강한 탄성을 갖는 입자로 표현하였다. 초기에 간과 간전이 후보 영역을 나타내는 입자들은 입력 영상의 해당 영역에 위치되며, 정합하고자 하는 대상 영상으로 부터 경사도 벡터 흐름(gradient vector flow) 방법으로 계산된 힘의 장을 따라 이동된다. 이 때, 각 입자는 간전이의 체적을 최대한 보존하기 위해 제안된 변형 가능 입자 방식에 따라 서로 물리적으로 상호작용하며 변형된다. 10명의 환자 데이터를 이용한 실험 결과에 따르면, 후속 컴퓨터 단층촬영(CT) 영상 간의 정합 과정에서 간의 모양을 효과적으로 일치시킬 뿐만 아니라 간전이의 체적을 거의 완벽하게 보존하여 간전이의 체적 변화를 정확하게 진단할 수 있게 하였다. 이 결과는 간전이 환자가 화학 요법을 시행 한 후 암의 진행 상태를 판단하기 위해 간전이의 크기 변화를 측정하는데 도움을 줄 수 있는 방법임을 시사한다.I. Introduction 1.1 Motivation 1 1.2 Dissertation Goals 3 1.3 Main Contribution 4 1.4 Organization of the Dissertation 5 II. Background 2.1 Medical Image Registration 6 2.1.1 Transformation Models 8 2.1.2 Similarity Metrics 18 2.1.3 Optimization 23 2.1.4 Physically Based Non-Rigid Registration 25 2.2 Smoothed Particle Hydrodynamics 29 2.2.1 Formulation of SPH 30 2.2.2 Kernels 33 2.2.3 Applications 35 III. Volume-Preserving Deformation of Particles 3.1 SPH for Deformable Objects 40 3.2 Volume-Preserving Deformable Particle 44 IV. Non-Rigid Registration with the Deformable Particles 4.1 Automatic Detection of Liver and Candidate Regions of Metastasis 50 4.2 Placement of Initial Particles in Source Image 53 4.3 Generation of GVF-based Force Field in Target Image 55 4.4 Non-Rigid Registration with Particles 58 4.5 Computation of Deformation Field 60 V. Implementation 5.1 Workflow 62 5.2 Neighbor Search 65 5.3 Time Integrator and Time Step 67 5.4 Terminating Condition 69 VI. Results 6.1 Phantom Study 71 6.2 General Observations based on Visual Assessment 73 6.3 Evaluation of Registration Performance 74 6.4 Evaluation of Metastasis Detection Accuracy 77 6.5 Evaluation of Volume Preservation 79 6.6 Parameter Study 80 VII. Conclusion 86 Bibliography 89Docto

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

Soft volume simulation using a deformable surface model

The aim of the research is to contribute to the modelling of deformable objects, such as soft tissues in medical simulation. Interactive simulation for medical training is a concept undergoing rapid growth as the underlying technologies support the increasingly more realstic and functional training environments. The prominent issues in the deployment of such environments centre on a fine balance between the accuracy of the deformable model and real-time interactivity. Acknowledging the importance of interacting with non-rigid materials such as the palpation of a breast for breast assessment, this thesis has explored the physics-based modelling techniques for both volume and surface approach. This thesis identified that the surface approach based on the mass spring system (MSS) has the benefits of rapid prototyping, reduced mesh complexity, computational efficiency and the support for large material deformation compared to the continuum approach. However, accuracy relative to real material properties is often over looked in the configuration of the resulting model. This thesis has investigated the potential and the feasibility of surface modelling for simulating soft objects regardless of the design of the mesh topology and the non-existence of internal volume discretisation. The assumptions of the material parameters such as elasticity, homogeneity and incompressibility allow a reduced set of material values to be implemented in order to establish the association with the surface configuration. A framework for a deformable surface model was generated in accordance with the issues of the estimation of properties and volume behaviour corresponding to the material parameters. The novel extension to the surface MSS enables the tensile properties of the material to be integrated into an enhanced configuration despite its lack of volume information. The benefits of the reduced complexity of a surface model are now correlated with the improved accuracy in the estimation of properties and volume behaviour. Despite the irregularity of the underlying mesh topology and the absence of volume, the model reflected the original material values and preserved volume with minimal deviations. Global deformation effect which is essential to emulate the run time behaviour of a real soft material upon interaction, such as the palpation of a generic breast, was also demonstrated, thus indicating the potential of this novel technique in the application of soft tissue simulation