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检索条件"任意字段=Conference on SPIE Image-Guided Procedures, Robotic Interventions, and Modeling"

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A Biomechanical approach for in vivo Lung Tumor Motion Prediction during External Beam Radiation Therapy

A Biomechanical approach for <i>in vivo</i> Lung Tumor Motio...

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conference on Medical Imaging - image-guided procedures, robotic interventions, and modeling

作者： Karami, Elham Gaede, Stewart Lee, Ting-Yim Samani, Abbas Univ Western Ontario Dept Med Biophys London ON Canada Robarts Res Inst Imaging Res Labs London ON N6A 5C1 Canada London Reg Canc Program Dept Phys & Engn London ON Canada Univ Western Ontario Dept Oncol London ON Canada Lawson Hlth Res Inst Imaging Program London ON Canada Univ Western Ontario Dept Med Imaging London ON Canada Univ Western Ontario Dept Elect & Comp Engn London ON Canada Univ Western Ontario Grad Program Biomed Engn London ON Canada

ISBN: (纸本)9781628415056

Lung Cancer is the leading cause of cancer death in both men and women. Among various treatment methods currently being used in the clinic, External Beam Radiation Therapy (EBRT) is used widely not only as the primary treatment method, but also in combination with chemotherapy and surgery. However, this method may lack desirable dosimetric accuracy because of respiration induced tumor motion. Recently, biomechanical modeling of the respiratory system has become a popular approach for tumor motion prediction and compensation. This approach requires reasonably accurate data pertaining to thoracic pressure variation, diaphragm position and biomechanical properties of the lung tissue in order to predict the lung tissue deformation and tumor motion. In this paper, we present preliminary results of an in vivo study obtained from a Finite Element Model (FEM) of the lung developed to predict tumor motion during respiration.

关键词： Lung Tumors Motion models Tissues 3D modeling In vivo imaging Data modeling Lung cancer Radiotherapy Finite element methods

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Two new ad-hoc models of detection physics and their evaluation for navigated beta probe surface imaging

Two new ad-hoc models of detection physics and their evaluat...

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conference on Medical Imaging - image-guided procedures, robotic interventions and modeling

作者： Shakir, Dzhoshkun I. Hartl, Alexander Schneider, Florian R. Pulko, Jozef Ziegler, Sibylle I. Navab, Nassir Lasser, Tobias Tech Univ Munich CAMP D-8000 Munich Germany Tech Univ Munich Nucl Med Dept Klin Rech Isar Munich Germany Tech Univ Munich Dept Phys Munich Germany

ISBN: (纸本)9780819489654

Intra-operative surface imaging with navigated beta probes in conjunction with positron-emitting radio-tracers like F-18-FDG has been shown to enable control of tumor resection borders. We showed previously that employing iterative reconstruction (MLEM) in conjunction with an ad-hoc model of the detection physics (based on solid-angle geometry, SA) improves the image quality. In this study, we sampled the beta probe readings of a point source using a precision step-motor to generate a look-up-table (LUT) model. We also generated a simplified geometrical model (SG) based on this data set. To see how these two models influence the image quality compared to the old SA model, we reconstructed images from sparsely sampled datasets of a phantom with three hotspots using each model. The images yielded 76% (SA), 81% (SG), and 81% (LUT) mean NCC compared to the ground truth. The SG and LUT models, however, could resolve the hotspots better in the datasets where the detector-to-phantom distance was larger. Additionally, we compared the deviations of the SA and SG analytical models to the measured LUT model, where we found that the SG model gives estimates substantially closer to the actual beta probe readings than the previous SA model.

关键词： Data modeling Seaborgium Physics image quality Statistical modeling Sensors Tumors Signal attenuation Instrument modeling Visualization

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Procedural wound geometry and blood flow generation for medical training simulators

Procedural wound geometry and blood flow generation for medi...

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conference on Medical Imaging - image-guided procedures, robotic interventions and modeling

作者： Aras, Rifat Shen, Yuzhong Li, Jiang Old Dominion Univ Dept Modeling Simulat & Visualizat Eng Norfolk VA 23529 USA Old Dominion Univ Dept Elect & Comp Engn Norfolk VA 23529 USA

ISBN: (纸本)9780819489654

Efficient application of wound treatment procedures is vital in both emergency room and battle zone scenes. In order to train first responders for such situations, physical casualty simulation kits, which are composed of tens of individual items, are commonly used. Similar to any other training scenarios, computer simulations can be effective means for wound treatment training purposes. For immersive and high fidelity virtual reality applications, realistic 3D models are key components. However, creation of such models is a labor intensive process. In this paper, we propose a procedural wound geometry generation technique that parameterizes key simulation inputs to establish the variability of the training scenarios without the need of labor intensive remodeling of the 3D geometry. The procedural techniques described in this work are entirely handled by the graphics processing unit (GPU) to enable interactive real-time operation of the simulation and to relieve the CPU for other computational tasks. The visible human dataset is processed and used as a volumetric texture for the internal visualization of the wound geometry. To further enhance the fidelity of the simulation, we also employ a surface flow model for blood visualization. This model is realized as a dynamic texture that is composed of a height field and a normal map and animated at each simulation step on the GPU. The procedural wound geometry and the blood flow model are applied to a thigh model and the efficiency of the technique is demonstrated in a virtual surgery scene.

关键词： procedural techniques wound geometry surface blood flow medical training simulators

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Model-based Risk Assessment for Motion Effects in 3D Radiotherapy of Lung Tumors

Model-based Risk Assessment for Motion Effects in 3D Radioth...

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conference on Medical Imaging - image-guided procedures, robotic interventions and modeling

作者： Werner, Rene Ehrhardt, Jan Schmidt-Richberg, Alexander Handels, Heinz Med Univ Lubeck Inst Med Informat D-23538 Lubeck Germany

ISBN: (纸本)9780819489654

Although 4D CT imaging becomes available in an increasing number of radiotherapy facilities, 3D imaging and planning is still standard in current clinical practice. In particular for lung tumors, respiratory motion is a known source of uncertainty and should be accounted for during radiotherapy planning - which is difficult by using only a 3D planning CT. In this contribution, we propose applying a statistical lung motion model to predict patients' motion patterns and to estimate dosimetric motion effects in lung tumor radiotherapy if only 3D images are available. Being generated based on 4D CT images of patients with unimpaired lung motion, the model tends to overestimate lung tumor motion. It therefore promises conservative risk assessment regarding tumor dose coverage. This is exemplarily evaluated using treatment plans of lung tumor patients with different tumor motion patterns and for two treatment modalities (conventional 3D conformal radiotherapy and step-&-shoot intensity modulated radiotherapy). For the test cases, 4D CT images are available. Thus, also a standard registration-based 4D dose calculation is performed, which serves as reference to judge plausibility of the model-based 4D dose calculation. It will be shown that, if combined with an additional simple patient-specific breathing surrogate measurement (here: spirometry), the model-based dose calculation provides reasonable risk assessment of respiratory motion effects.

关键词： motion estimation registration modeling radiotherapy

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Geometric modeling of the Aortic Inner and Outer Vessel Wall from CTA for Aortic Dissection Analysis

Geometric Modeling of the Aortic Inner and Outer Vessel Wall...

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conference on Medical Imaging - image-guided procedures, robotic interventions, and modeling

作者： Eigen, Katharina Weis, Michael Dohle, Daniel-Sebastian Suehling, Michael Maier, Andreas Friedrich Alexander Univ Erlangen Nuremberg Erlangen Germany Siemens Healthcare GmbH Forchheim Germany Univ Med Ctr Mainz Germany

ISBN: (数字)9781510616424

ISBN: (纸本)9781510616424

In this paper, we present a novel method for modeling both layers of the aortic walls in cases of aortic dissections for analysis from Computed Tomography Angiography. It involves a fast initialization of the associated physiological and pathological lumina and further editing on non-linearly formatted and cross-sectional views. Fast and accurate derivation of 3D models of these inner and outer vessel walls is crucial to analyze true and false lumen, to accelerate processing times in research studies, and to answer therapy questions. Since the aorta is a relatively large vessel, our system makes use of a point-based surface interpolation with compactly supported radial basis functions requiring only few surface constraints. Where possible, we use a semi-automatic approach to segment the vessel walls using an Active Contour Model, which detects the contours in the vessel's cross-sectional planes, stating the constraints for interpolation. After initialization, editing on non-linearly formatted and cross-sectional views is possible due to handling user input through tangent frame bundles to dismiss contradictory surface samples before updating the models with the new constraints. Our proposed method was evaluated in a user study to measure processing times and achievable model accuracy with respect to an expert-defined ground truth. The users needed 19 minutes on average to derive one model (both walls) and attained a mean surface distance of about 1.0 mm for the outer vessel wall, respectively, 1.6 mm for the inner wall. Using our method instead of open source program for geometric modeling saves 26 minutes per dataset.

关键词： Aortic Dissection Active Contour Model Tangent Frame Bundles

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Neurosurgery Simulation Using Non-linear Finite Element modeling and Haptic Interaction

Neurosurgery Simulation Using Non-linear Finite Element Mode...

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conference on Medical Imaging - image-guided procedures, robotic interventions and modeling

作者： Lee, Huai-Ping Audette, Michel Joldes, Grand Roman Enquobahrie, Andinet Kitware Inc Clifton Pk NY 12065 USA Univ N Carolina Dept Comp Sci Chapel Hill NC 27599 USA Old Dominion Univ Dept MSVE Norfolk VA 23529 USA Univ Western Australia Sch Mech Engn Perth WA Australia

ISBN: (纸本)9780819489654

Real-time surgical simulation is becoming an important component of surgical training. To meet the real-time requirement, however, the accuracy of the biomechancial modeling of soft tissue is often compromised due to computing resource constraints. Furthermore, haptic integration presents an additional challenge with its requirement for a high update rate. As a result, most real-time surgical simulation systems employ a linear elasticity model, simplified numerical methods such as the boundary element method or spring-particle systems, and coarse volumetric meshes. However, these systems are not clinically realistic. We present here an on-going work aimed at developing an efficient and physically realistic neurosurgery simulator using a non-linear finite element method (FEM) with haptic interaction. Real-time finite element analysis is achieved by utilizing the total Lagrangian explicit dynamic (TLED) formulation and GPU acceleration of per-node and per-element operations. We employ a virtual coupling method for separating deformable body simulation and collision detection from haptic rendering, which needs to be updated at a much higher rate than the visual simulation. The system provides accurate biomechancial modeling of soft tissue while retaining a real-time performance with haptic interaction. However, our experiments showed that the stability of the simulator depends heavily on the material property of the tissue and the speed of colliding objects. Hence, additional efforts including dynamic relaxation are required to improve the stability of the system.

关键词： surgical simulation non-linear biomechanics finite element method haptic rendering

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Automatic localization of the internal auditory canal for patient-specific cochlear implant modeling

Automatic localization of the internal auditory canal for pa...

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conference on Medical Imaging - image-guided procedures, robotic interventions, and modeling

作者： Alduraibia, Ghassan I. Banalagaya, Rueben Labadieb, Robert F. Noblea, Jack H. Vanderbilt Univ Dept Elect Engn & Comp Sci 221 Kirkland Hall Nashville TN 37235 USA Vanderbilt Univ Med Ctr Dept Otolaryngol Head & Neck Surg Nashville TN 37232 USA

ISBN: (纸本)9781510625501

Cochlear implants (CIs) use a surgically implanted electrode array to treat severe-to-profound sensorineural hearing loss. Audiologists program CIs by selecting a number of stimulation parameters for the CI processor to optimize hearing performance. It has been shown in previous research that audiologists arrive at CI settings that lead to a better hearing outcome when they are provided an estimate of which regions of the auditory nerve are being activated by each electrode for a patient. If the neural fibers could be localized, neural fiber models could be used to estimate activation in response to electrode activation for individual patients. However, the neural fibers are so small they are not visible in clinical images. In this project, our aim is to develop an active-shape model based solution to automatically localize the Internal Auditory Canal (IAC), which houses the auditory nerves and has borders that are visible in CT scans, to serve as a landmark for localizing the nerve fibers. Seven manually segmented IAC volumes were used to create and validate our method using a leave-one-out approach. We found that the mean surface errors of the dataset ranged from similar to 0.4 to similar to 1.2 CT voxels (0.13 mm to 0.37 mm). These results suggest that our IAC segmentation is highly accurate and could provide an excellent landmark for estimating fiber position.

关键词： Internal auditory canal active shape model cochlear implant auditory nerve image segmentation

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Evaluation of three 3D US calibration methods

Evaluation of three 3D US calibration methods

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conference on Medical Imaging - image-guided procedures, robotic interventions, and modeling

作者： Hummel, Johann Kaar, Marcus Hoffmann, Rainer Bhatia, Amon Birkfellner, Wolfgang Figl, Michael Med Univ Vienna Ctr Med Phys & Biomed Engn Vienna Austria

ISBN: (纸本)9780819494450

With the introduction of 3D US image devices the demand for accurate and fast 3D calibration methods arose. We implemented three different calibration methods and compared the calibration results in terms of fiducial registration error (FRE) and target registration error (TRE). The three calibration methods included a multi-points phantom (MP), a feature based model (FM) and a membrane model (MM). With respect to the sphere method a simple point-to-point registration was applied. For the feature based model we employed a phantom consisting of spheres, pyramids and cones. These objects were imaged from different angles and a 3D3D registration was applied for all possible image combinations. The last method was accomplished by imaging a simple membrane which allows for calculation of the calibration matrix. For a first evaluation we computed the FRE for each method. To assess the calibration success on real patient data we used ten 3D3D registrations between images from the prostate. The FRE for the sphere method amounted to 1.40 mm, for the figure method to 1.05 mm and with respect to the membrane method to 1.12 mm. The deviation arising from ten 3D3D patient registration were 3.44 mm (MP), 2.93 mm (FM)and 2.84 mm (MM). The MM revealed to be the most accurate of the evaluated procedure while the MP has shown significant higher errors. The results from FM were close to the one from MM and also significant better than the one with the SM. Between FM and MM no significant difference was to detect.

关键词： Calibration image registration Optical spheres Ultrasonography Fermium Frequency modulation 3D image processing 3D acquisition 3D modeling Optical tracking

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Medical Imaging 2019: image-guided procedures, robotic interventions, and modeling

Medical Imaging 2019: Image-Guided Procedures, Robotic Inter...

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Medical Imaging 2019: image-guided procedures, robotic interventions, and modeling

ISBN: (纸本)9781510625495

The proceedings contain 106 papers. The topics discussed include: visual SLAM for bronchoscope tracking and bronchus reconstruction in bronchoscopic navigation;automatic marker-free target positioning and tracking for image-guided radiotherapy and interventions;optimal intermittent measurements for tumor tracking in X-ray guided radiotherapy;quantitative assessment of the relationship between myocardial lesion formation detected by delayed contrast-enhanced magnetic resonance imaging and proton beam planning dose for treatment of ventricular tachycardia;LV systolic point-cloud model to quantify accuracy of CT derived regional strain;designing lightweight deep learning models for echocardiography view classification;a dynamic neonatal heart phantom for ultrafast color Doppler echocardiography evaluation;and a dynamic mitral valve simulator for surgical training and patient specific preoperative planning.

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Dynamic Optical Contrast Imaging (DOCI): System theory for rapid, wide-field, multispectral optical imaging using fluorescence lifetime contrast mechanism

Dynamic Optical Contrast Imaging (DOCI): System theory for r...

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conference on Medical Imaging - image-guided procedures, robotic interventions, and modeling

作者： Cheng, Harrison Xie, Yao Pellionisz, Peter Pearigen, Aidan Rangwalla, Khuzaima Stafsudd, Oscar Taylor, Zachary St John, Maie Grundfest, Warren Univ Calif Los Angeles Dept Bioengn Henry Samueli Sch Engn & Appl Sci Los Angeles CA 90095 USA Univ Calif Los Angeles Dept Elect & Comp Engn Henry Samueli Sch Engn & Appl Sci Los Angeles CA USA Aalto Univ Dept Elect & Nanoengn Helsinki Finland Univ Calif Los Angeles David Geffen Sch Med Dept Head & Neck Surg Los Angeles CA 90095 USA

ISBN: (纸本)9781510625501

Dynamic Optical Contrast Imaging (DOCI) is an imaging technique that generates image contrast through ratiometric measurements of the autofluorescence decay rates of aggregate fluorophores in tissue. This method enables better tissue characterization by utilizing wide-field signal integration, eliminating constraints of uniform illumination, and reducing time-intensive computations that are bottlenecks in the clinical translation of traditional fluorescence lifetime imaging. Previous works have demonstrated remarkable tissue contrast between tissue types in clinical human pilot studies. However, there are still challenges in the development of several subsystems, which results in existing works to use relative models. A comprehensive mathematical framework is presented to describe the contrast mechanism of the DOCI system to allow intraoperative quantitative imaging, which merits consideration for evaluation in measuring tissue characteristics in several important clinical settings.

关键词： spie Proceedings Dynamic Optical Contrast Imaging Fluorescence Lifetime System Theory Real-time Imaging

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