Efficient computational fluid dynamics mesh generation by image registration (original) (raw)
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From medical images to computational meshes
Numerical simulations take a bigger importance in medical activity as they allow to obtain information non-invasively. To take into account individual variability, we propose numerical simulations in geometries reconstructed from medical images. We present the necessary treatment of images of diseased vessels, to provide a computational mesh of an anatomical model of the subject. First a faceted surface is extracted from the images. Then this surface is transformed into a geometrical model to be finally remeshed for a finite element use.
From medical images to anatomically accurate finite element grids
International Journal for Numerical Methods in Engineering, 2001
The successful application of computational modelling of blood ow for the planning of surgical and interventional procedures to treat cardiovascular diseases strongly depends on the rapid construction of anatomical models. The large individual variability of the human vasculature and the strong dependence of blood ow characteristics on the vessel geometry require modelling on a patient-specic basis. Various image processing and geometrical modelling techniques are integrated for the rapid construction of geometrical surface models of arteries starting from medical images. These discretely dened surfaces are then used to generate anatomically accurate nite element grids for hemodynamic simulations. The proposed methodology operates directly in 3D and consists of three stages. In the rst stage, the images are ltered to reduce noise and segmented using a region-growing algorithm in order to obtain a properly dened boundary of the arterial lumen walls. In the second stage, a surface triangulation representing the vessel walls is generated using a direct tessellation of the boundary voxels. This surface is then smoothed and the quality of the resulting triangulation is improved. Finally, in the third stage, the triangulation is subdivided into so-called discrete surface patches for surface gridding, the desired element size distribution is dened and the nite element grid generated. Copyright ? 2001 John Wiley & Sons, Ltd.
FLUCOME'07, 9 …, 2007
A new thrust in the use of CFD techniques for simulation of biological flows has necessitated the demand for robust grid generation techniques to characterize the complex geometries. While the techniques of image manipulation required are simple, most researchers in this field use proprietary 3rd party software for image manipulation and grid generation. In the current study we propose a simple MATLAB based grid generation techniques suitable for CFD studies of external and internal flows such as blood flow and respiration and flows around the human body. As an example the flow inside two specific intracranial aneurysms is modeled by generating CFD grids from 3D rotational angiography images. Specific issues of modeling, such as boundary conditions and location of flow inlets and outlets, in relation to the reconstructed geometry, are discussed. The reconstructed arterial geometry including the aneurysm matches the visual representation generated by the angiogram software (Leonardo software). The calculated CFD flow patterns also show a good correlation to the flow visualization presented by the Leonardo software. Areas of high pressure and wall shear stress are identified. The same technique is also used to generate the CFD grid of a human trachea to study the particle dispersion patterns during a human cough cycle. The fluid is modeled using an actual human cough signal with the particles simulating the influenza virus. The flow pattern out of the mouth along with the dispersion pattern of the particles is validated against similar human experimental studies to track the spread of the disease through cough. Work is also currently underway to use the present grid generation program to construct a superficial mesh for human body from cadaver images. The goal is to build an accurate and scalable model of the human body surface with articulate joints which can be posed in any environment to model the air flow patterns around the body.
CFD mesh generation for biological flows: Geometry reconstruction using diagnostic images
Computers & Fluids, 2009
A new thrust in the use of CFD techniques for simulation of biological flows has necessitated the demand for robust grid generation techniques to characterize the complex geometries. While the techniques of image manipulation required are simple, most researchers in this field use proprietary 3rd party software for image manipulation and grid generation. In the current study, we propose a simple MATLAB based grid generation techniques suitable for CFD studies of external and internal biological flows such as blood flow and respiration and flows around the human body. As an example, the flow inside two specific intracranial aneurysms is modeled by generating CFD grids from 3D rotational angiography images. Specific issues of modeling, such as boundary conditions and location of flow inlets and outlets, in relation to the reconstructed geometry are discussed. The reconstructed arterial geometry including the aneurysm matches the visual representation generated by the angiogram software (Leonardo software). The calculated CFD flow patterns also show a good correlation to the flow visualization presented by the Leonardo software. Areas of high pressure and wall shear stress are identified. The same technique is also used to generate the CFD grid of a human trachea to study the particle dispersion patterns during a human cough cycle. The fluid is modeled using an actual human cough signal with the particles simulating the influenza virus. The flow pattern out of the mouth along with the dispersion pattern of the particles is validated against similar human experimental studies to track the spread of the disease through cough. Work is also currently underway to use the present grid generation program to construct a superficial mesh of the human body from MRI/CAT scan images of cadavers. The goal is to build an accurate and scalable model of the human body surface with articulate joints which can be posed in any environment to model the air flow patterns around the body.
4D Image-Based CFD Simulation of Compliant Blood Vessel
2010
Numerical simulation of fluid-structure interaction (FSI) in the arterial system is a challenging and time consuming procedure because of the intrinsic heterogeneous nature of the problem. Moreover, in patientspecific simulations, modeling of the vascular structure requires parameter identification still difficult to accomplish. On the other hand, new imaging devices provide time sequences of the moving vessel of interest. When one is interested only in the blood dynamics in the compliant vessel, a possible alternative to the full fluid-structure interaction simulation is to track the vessel displacement from the images and then to solve the fluid problem in the moving domain reconstructed accordingly. In this paper, we present an example of this image-based technique. We describe the steps necessary for this approach (image acquisition and 3D geometric reconstruction, motion tracking, computational fluid dynamics (CFD) simulation) and present some results referring to an aortic arch and a validation of the proposed technique vs. a traditional FSI simulation in a carotid bifurcation. This approach significantly reduces the CPU time since the dynamics of the structure is retrieved from the images instead of being numerically computed. This work places itself in the framework of a strong integration between data (images/measures) and simulations that is likely to introduce a significant improvement in the reliability of cardiovascular numerical mathematics. . Prepared using cnmauth.cls [Version: 2010/03/27 v2.00] 2 M. PICCINELLI ET AL for healthy subjects. The nonlinearities of the model result however in computational difficulties.
Semi-automatic surface and volume mesh generation for subject-specific biomedical geometries
International Journal For Numerical Methods in Biomedical Engineering, 2012
An overview of surface and volume mesh generation techniques for creating valid meshes to carry out biomedical flows is provided. The methods presented are designed for robust numerical modelling of biofluid flow through subject-specific geometries. The applications of interest are haemodynamics in blood vessels and air flow in upper human respiratory tract. The methods described are designed to minimize distortion to a given domain boundary. They are also designed to generate a triangular surface mesh first and then volume mesh (tetrahedrons) with high quality surface and volume elements. For blood flow applications, a simple procedure to generate a boundary layer mesh is also described. The methods described here are semiautomatic in nature because of the fact that the geometries are complex, and automation of the procedures may be possible if high quality scans are used. of a well-defined object and patient-specific geometry is in building the surface mesh. Because the surface is not analytically defined in subject-specific applications, alternative approaches to that of the standard geometries are required.
Numerical treatment of registration problem in generation of patient-specific anatomical models.„
Journal of Medical Informatics and …, 2003
Registration is an important component of many medical data processing applications. Particularly significant is its role in the correlation of volumetric medical data aiming at generation of virtual patient-specific anatomical models. Such models enable optimization of various diagnostic and therapeutical procedures. The importance of the virtual patient models is becoming increasingly recognized in modern medicine. The advantages of using such biomedical virtual models are analogous to the advantages of real system behavior simulation in the engineering or material sciences. In this work some numerical issues associated with the registration problem and the visualization challenges arising in the context of virtual anatomical models have been presented and discussed.
Medical imaging techniques, such as MRI and CT scanning, are valuable tools for reconstructing the geometry of complex objects. Much effort has been applied in the biomechanical research field to develop image processing software capable of generating valid meshes for computational continuum mechanics packages from such scans. To date these techniques have largely been applied to computation of single physical processes, e.g., fluid flow or stress analysis. We describe techniques for image to mesh conversion which permit the creation of multiple meshes for distinct volumes of the object, ensuring absolute conformity between the meshes on shared boundaries and allowing computation of coupled physical processes on distinct subregions of the total volume. Such techniques have application well beyond the biomedical field, and we illustrate the possibilities with coupled fluid flow/heat transfer calculations for an apple pie and a metal foam. Keywords: Mesh generation; Computational Fluid Dynamics; heat transfer
Generation and adaptation of computational surface meshes from discrete anatomical data
International Journal for Numerical Methods in Engineering, 2004
Fast and accurate scanning devices are nowadays widely used in many engineering and biomedical fields. The resulting discrete data is usually directly converted into polygonal surface meshes, using 'brute-force' algorithms, often resulting in meshes that may contain several millions of polygons. Simplification is therefore required in order to make storage, computation and display possible if not efficient. In this paper, we present a general scheme for mesh simplification and optimization that allows to control the geometric approximation as well as the element shape and size quality (required for numerical simulations). Several examples ranging from academic to complex biomedical geometries (organs) are presented to illustrate the efficiency and the utility of the proposed approach.
Acquisition of 3-D Arterial Geometries and Integration with Computational Fluid Dynamics
Ultrasound in Medicine & Biology, 2009
A system for acquisition of 3-D arterial ultrasound geometries and integration with computational fluid dynamics (CFD) is described. The 3-D ultrasound is based on freehand B-mode imaging with positional information obtained using an optical tracking system. A processing chain was established, allowing acquisition of cardiacgated 3-D data and segmentation of arterial geometries using a manual method and a semi-automated method, 3D meshing and CFD. The use of CFD allowed visualization of flow streamlines, 2-D velocity contours and 3-D wall shear stress. Three-dimensional positional accuracy was 0.17-1.8 mm, precision was 0.06-0.47 mm and volume accuracy was 4.4-15%. Patients with disease and volunteers were scanned, with data collection from one or more of the carotid bifurcation, femoral bifurcation and abdominal aorta. An initial comparison between a manual segmentation method and a semi-automated method suggested some advantages to the semi-automated method, including reduced operator time and the production of smooth surfaces suitable for CFD, but at the expense of over-smoothing in the diseased region. There were considerable difficulties with artefacts and poor image quality, resulting in 3-D geometry data that was unsuitable for CFD. These artefacts were exacerbated in disease, which may mean that future effort, in the integration of 3-D arterial geometry and CFD for clinical use, may best be served using alternative 3-D imaging modalities such as magnetic resonance imaging and computed tomography.