166 research outputs found

    Research on real-time physics-based deformation for haptic-enabled medical simulation

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    This study developed a multiple effective visuo-haptic surgical engine to handle a variety of surgical manipulations in real-time. Soft tissue models are based on biomechanical experiment and continuum mechanics for greater accuracy. Such models will increase the realism of future training systems and the VR/AR/MR implementations for the operating room

    COMPUTATIONAL ULTRASOUND ELASTOGRAPHY: A FEASIBILITY STUDY

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    Ultrasound Elastography (UE) is an emerging set of imaging modalities used to assess the biomechanical properties of soft tissues. UE has been applied to numerous clinical applications. Particularly, results from clinical trials of UE in breast lesion differentiation and staging liver fibrosis indicated that there was a lack of confidence in UE measurements or image interpretation. Confidence on UE measurements interpretation is critically important for improving the clinical utility of UE. The primary objective of my thesis is to develop a computational simulation platform based on open-source software packages including Field II, VTK, FEBio and Tetgen. The proposed virtual simulation platform can be used to simulate SE and acoustic radiation force based SWE simulations, including pSWE, SSI and ARFI. To demonstrate its usefulness, in this thesis, examples for breast cancer detections were provided. The simulated results can reproduce what has been reported in the literature. To statistically analyze the intrinsic variations of shear wave speed (SWS) in the fibrotic liver tissues, a probability density function (PDF) of the SWS distribution in conjunction with a lossless stochastic tissue model was derived using the principle of Maximum Entropy (ME). The performance of the proposed PDF was evaluated using Monte-Carlo (MC) simulated shear wave data and against three other commonly used PDFs. We theoretically demonstrated that SWS measurements follow a non-Gaussian distribution for the first time. One advantage of the proposed PDF is its physically meaningful parameters. Also, we conducted a case study of the relationship between shear wave measurements and the microstructure of fibrotic liver tissues. Three different virtual tissue models were used to represent underlying microstructures of fibrotic liver tissues. Furthermore, another innovation of this thesis is the inclusion of “biologically-relevant” fibrotic liver tissue models for simulation of shear wave elastography. To link tissue structure, composition and architecture to the ultrasound measurements directly, a “biologically relevant” tissue model was established using Systems Biology. Our initial results demonstrated that the simulated virtual liver tissues qualitatively could reproduce histological results and wave speed measurements. In conclusions, these computational tools and theoretical analysis can improve the confidence on UE image/measurements interpretation

    Automatic Food Intake Assessment Using Camera Phones

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    Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user\u27s memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors

    Development of a statistical shape and appearance model of the skull from a South African population

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    Statistical shape models (SSMs) and statistical appearance models (SAMs) have been applied in medical analysis such as in surgical planning, finite element analysis, model-based segmentation, and in the fields of anthropometry and forensics. Similar applications can make use of SSMs and SAMs of the skull. A combination of the SSM and SAM of the skull can also be used in model-based segmentation. This document presents the development of a SSM and a SAM of the human skull from a South African population, using the Scalismo software package. The SSM development pipeline was composed of three steps: 1) Image data segmentation and processing; 2) Development of a free-form deformation (FFD) model for establishing correspondence across the training dataset; and 3) Development and validation of a SSM from the corresponding dataset. The SSM was validated using the leave one-out cross-validation method. The first eight principal components of the SSM represented 92.13% of the variation in the model. The generality of the model in terms of the Hausdorff distance between a new shape generated by the SSM and instances of the SSM had a steady state value of 1.48mm. The specificity of the model (in terms of Hausdorff distance) had a steady state value of 2.04mm. The SAM development pipeline involved four steps: 1) Volumetric mesh generation of the reference mesh to be used in establishing volumetric correspondence; 2) Sampling of intensity values from original computed tomography (CT) images using the in-correspondence volumetric meshes; and 3) Development of a SAM from the in-correspondence intensity values. A complete validation of the SAM was not possible due to limitations of the Scalismo software. As a result, only the shapes of the incomplete skulls were reconstructed and thereby validated. The amount of missing detail, as represented by absent landmarks, affected the registration results. Complete validation of the SAM is recommended as future work, via the use of a combined shape and intensity model (SSIM)

    A fast and robust patient specific Finite Element mesh registration technique: application to 60 clinical cases

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    Finite Element mesh generation remains an important issue for patient specific biomechanical modeling. While some techniques make automatic mesh generation possible, in most cases, manual mesh generation is preferred for better control over the sub-domain representation, element type, layout and refinement that it provides. Yet, this option is time consuming and not suited for intraoperative situations where model generation and computation time is critical. To overcome this problem we propose a fast and automatic mesh generation technique based on the elastic registration of a generic mesh to the specific target organ in conjunction with element regularity and quality correction. This Mesh-Match-and-Repair (MMRep) approach combines control over the mesh structure along with fast and robust meshing capabilities, even in situations where only partial organ geometry is available. The technique was successfully tested on a database of 5 pre-operatively acquired complete femora CT scans, 5 femoral heads partially digitized at intraoperative stage, and 50 CT volumes of patients' heads. The MMRep algorithm succeeded in all 60 cases, yielding for each patient a hex-dominant, Atlas based, Finite Element mesh with submillimetric surface representation accuracy, directly exploitable within a commercial FE software

    RNA AS A UNIQUE POLYMER TO BUILD CONTROLLABLE NANOSTRUCTURES FOR NANOMEDICINE AND NANOTECHNOLOGY

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    RNA nanotechnology is an emerging field that involves the design, construction and functionalization of nanostructures composed mainly of RNA for applications in biomedical and material sciences. RNA is a unique polymer with structural simplicity like DNA and functional diversity like proteins. A variety of RNA nanostructures have been reported with different geometrical structures and functionalities. This dissertation describes the design and construction of novel two-dimensional and three-dimensional self-assembled RNA nanostructures with applications in therapeutics delivery, cancer targeting and immunomodulation. Firstly, by using the ultra-stable pRNA three-way junction motif with controllable angles and arm lengths, tetrahedral architectures composed purely of RNA were successfully assembled via one-pot bottom-up assembly with high efficiency and thermal stability. By introducing arm sizes of 22 bp and 55 bp, two RNA tetrahedrons with similar global contour structure but with different sizes of 8 nm and 17 nm were successfully assembled. The RNA tetrahedrons were also highly amenable to functionalization. Fluorogenic RNA aptamers, ribozyme, siRNA, and protein-binding RNA aptamers were integrated into the tetrahedrons by simply fusing the respective sequences with the tetrahedral core modules. Secondly, I reported the design and construction of molecularly defined RNA cages with cube and dodecahedron shapes based on the stable pRNA 3WJ. The RNA cages can be easily self-assembled by single-step annealing. The RNA cages were further characterized by gel electrophoresis, cryo-electron microscopy and atomic force microscopy, confirming the spontaneous formation of the RNA cages. I also demonstrated that the constructed RNA cages could be used to deliver model drugs such as immunomodulatory CpG DNA into cells and elicit enhanced immune responses. Thirdly, by using the modular multi-domain strategy, molecular defined RNA nanowires can be successfully self-assembled via a bottom-up approach. Only four different 44-nucleotide single-stranded RNAs were used to assemble the RNA nanowire. The reported RNA nanowire has the potential to be explored in the future as the carrier for drug delivery or matrix for tissue engineering. Fourthly, the construction of RNA polygons for delivering immunoactive CpG oligonucleotides will be presented. When CpG oligonucleotides were incorporated into the RNA polygons, their immunomodulation effect for cytokine TNF-α and IL-6 induction was greatly enhanced, while RNA polygon controls induced unnoticeable cytokine induction. Moreover, the RNA polygons were delivered to macrophages specifically and the degree of immunostimulation greatly depended on the size, shape, and the number of payload per RNA polygon. Collectively, these findings demonstrated RNA nanotechnology can produce controllable nanostructures with different functionalities and result in potential applications in nanomedicine and nanotechnology

    Modified mass-spring system for physically based deformation modeling

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    Mass-spring systems are considered the simplest and most intuitive of all deformable models. They are computationally efficient, and can handle large deformations with ease. But they suffer several intrinsic limitations. In this book a modified mass-spring system for physically based deformation modeling that addresses the limitations and solves them elegantly is presented. Several implementations in modeling breast mechanics, heart mechanics and for elastic images registration are presented

    Modified mass-spring system for physically based deformation modeling

    Get PDF
    Mass-spring systems are considered the simplest and most intuitive of all deformable models. They are computationally efficient, and can handle large deformations with ease. But they suffer several intrinsic limitations. In this book a modified mass-spring system for physically based deformation modeling that addresses the limitations and solves them elegantly is presented. Several implementations in modeling breast mechanics, heart mechanics and for elastic images registration are presented

    Monotone methods on non-matching grids for non-linear contact problems

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    Nonconforming domain decomposition techniques provide a powerful tool for the numerical approximation of partial differential equations. We use a generalized mortar method based on dual Lagrange multipliers for the discretization of a nonlinear contact problem between linear elastic bodies. In the case of unilateral contact problems, pointwise constraints occur and monotone multigrid methods yield efficient iterative solvers. Here, we generalize these techniques to nonmatching triangulations, where the constraints are realized in terms of weak integral conditions. The basic new idea is the construction of a nested sequence of nonconforming constrained spaces. We use suitable basis transformations and a multiplicative correction. In contrast to other approaches, no outer iteration scheme is required. The resulting monotone method is of optimal complexity and can be implemented as a multigrid method. Numerical results illustrate the performance of our approach in two and three dimensions
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