79 resultados para Virtual 3D model
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Background: Statistical shape models are widely used in biomedical research. They are routinely implemented for automatic image segmentation or object identification in medical images. In these fields, however, the acquisition of the large training datasets, required to develop these models, is usually a time-consuming process. Even after this effort, the collections of datasets are often lost or mishandled resulting in replication of work. Objective: To solve these problems, the Virtual Skeleton Database (VSD) is proposed as a centralized storage system where the data necessary to build statistical shape models can be stored and shared. Methods: The VSD provides an online repository system tailored to the needs of the medical research community. The processing of the most common image file types, a statistical shape model framework, and an ontology-based search provide the generic tools to store, exchange, and retrieve digital medical datasets. The hosted data are accessible to the community, and collaborative research catalyzes their productivity. Results: To illustrate the need for an online repository for medical research, three exemplary projects of the VSD are presented: (1) an international collaboration to achieve improvement in cochlear surgery and implant optimization, (2) a population-based analysis of femoral fracture risk between genders, and (3) an online application developed for the evaluation and comparison of the segmentation of brain tumors. Conclusions: The VSD is a novel system for scientific collaboration for the medical image community with a data-centric concept and semantically driven search option for anatomical structures. The repository has been proven to be a useful tool for collaborative model building, as a resource for biomechanical population studies, or to enhance segmentation algorithms.
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Nucleus pulposus (NP) regeneration by the application of injectable cell-embedded hydrogels is an appealing approach for tissue engineering. We investigated a thermo-reversible hydrogel (TR-HG), based on a modified polysaccharide with a thermo-reversible polyamide [poly(N-isopropylacrylamide), pNIPAM], which is made to behave as a liquid at room temperature and hardens at > 32 °C. In order to test the hydrogel, a papain-induced bovine caudal disc degeneration model (PDDM), creating a cavity in the NP, was employed. Human mesenchymal stem cells (hMSCs) or autologous bovine NP cells (bNPCs) were seeded in TR-HG; hMSCs were additionally preconditioned with rhGDF-5 for 7 days. Then, TR-HG was reversed to a fluid and the cell suspension injected into the PDDM and kept under static loading for 7 days. Experimental design was: (D1) fresh disc control + PBS injection; (D2) PDDM + PBS injection; (D3) PDDM + TR-HG (material control); (D4) PDDM + TR-HG + bNPCs; (D5) PDDM + TR-HG + hMSCs. Magnetic resonance imaging performed before and after loading, on days 9 and 16, allowed imaging of the hydrogel-filled PDDM and assessment of disc height and volume changes. In gel-injected discs the NP region showed a major drop in volume and disc height during culture under static load. The RT–PCR results of injected hMSCs showed significant upregulation of ACAN, COL2A1, VCAN and SOX9 during culture in the disc cavity, whereas the gene expression profile of NP cells remained unchanged. The cell viability of injected cells (NPCs or hMSCs) was maintained at over 86% in 3D culture and dropped to ~72% after organ culture. Our results underline the need for load-bearing hydrogels that are also cyto-compatible.
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Background: The design of Virtual Patients (VPs) is essential. So far there are no validated evaluation instruments for VP design published. Summary of work: We examined three sources of validity evidence of an instrument to be filled out by students aimed at measuring the quality of VPs with a special emphasis on fostering clinical reasoning: (1) Content was examined based on theory of clinical reasoning and an international VP expert team. (2) Response process was explored in think aloud pilot studies with students and content analysis of free text questions accompanying each item of the instrument. (3) Internal structure was assessed by confirmatory factor analysis (CFA) using 2547 student evaluations and reliability was examined utilizing generalizability analysis. Summary of results: Content analysis was supported by theory underlying Gruppen and Frohna’s clinical reasoning model on which the instrument is based and an international VP expert team. The pilot study and analysis of free text comments supported the validity of the instrument. The CFA indicated that a three factor model comprising 6 items showed a good fit with the data. Alpha coefficients per factor were 0,74 - 0,82. The findings of the generalizability studies indicated that 40-200 student responses are needed in order to obtain reliable data on one VP. Conclusions: The described instrument has the potential to provide faculty with reliable and valid information about VP design. Take-home messages: We present a short instrument which can be of help in evaluating the design of VPs.
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Reconstruction of shape and intensity from 2D x-ray images has drawn more and more attentions. Previously introduced work suffers from the long computing time due to its iterative optimization characteristics and the requirement of generating digitally reconstructed radiographs within each iteration. In this paper, we propose a novel method which uses a patient-specific 3D surface model reconstructed from 2D x-ray images as a surrogate to get a patient-specific volumetric intensity reconstruction via partial least squares regression. No DRR generation is needed. The method was validated on 20 cadaveric proximal femurs by performing a leave-one-out study. Qualitative and quantitative results demonstrated the efficacy of the present method. Compared to the existing work, the present method has the advantage of much shorter computing time and can be applied to both DXA images as well as conventional x-ray images, which may hold the potentials to be applied to clinical routine task such as total hip arthroplasty (THA).
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The unique characteristics of special populations such as pre-school children and Down syndrome kids in crisis and their distorted self-image were never studied before, because of the difficulty of crisis reproduction. This study proposes a VR setting that tries to model some special population's behaviour in the time of crises and offers them a training scenario. The sample population consisted of 30 pre-school children and 20 children with Down syndrome. The VR setting involved a high-speed PC, a VPL EyePhone 1, a MR toolkit, a vibrations plate, a motion capture system and other sensors. The system measured and modelled the typical behaviour of these special populations in a Virtual Earthquake scenario with sight and sound and calculated a VR anthropomorphic model that reproduced their behaviour and emotional state. Afterwards one group received an emotionally enhanced VR self-image as feedback for their training, one group received a plain VR self-image and another group received verbal instructions. The findings strongly suggest that the training was a lot more biased by the emotionally enhanced VR self-image than the other approaches. These findings could highlight the special role of the self-image to therapy and training and the interesting role of imagination to emotions, motives and learning. Further studies could be done with various scenarios in order to measure the best-biased behaviour and establish the most natural and affective VR model. This presentation is going to highlight the main findings and some theories behind them.
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High throughput discovery of ligand scaffolds for target proteins can accelerate development of leads and drug candidates enormously. Here we describe an innovative workflow for the discovery of high affinity ligands for the benzodiazepine-binding site on the so far not crystallized mammalian GABAA receptors. The procedure includes chemical biology techniques that may be generally applied to other proteins. Prerequisites are a ligand that can be chemically modified with cysteine-reactive groups, knowledge of amino acid residues contributing to the drug-binding pocket, and crystal structures either of proteins homologous to the target protein or, better, of the target itself. Part of the protocol is virtual screening that without additional rounds of optimization in many cases results only in low affinity ligands, even when a target protein has been crystallized. Here we show how the integration of functional data into structure-based screening dramatically improves the performance of the virtual screening. Thus, lead compounds with 14 different scaffolds were identified on the basis of an updated structural model of the diazepam-bound state of the GABAA receptor. Some of these compounds show considerable preference for the α3β2γ2 GABAA receptor subtype.
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Background: Virtual patients (VPs) are increasingly used to train clinical reasoning. So far, no validated evaluation instruments for VP design are available. Aims: We examined the validity of an instrument for assessing the perception of VP design by learners. Methods: Three sources of validity evidence were examined: (i) Content was examined based on theory of clinical reasoning and an international VP expert team. (ii) The response process was explored in think-aloud pilot studies with medical students and in content analyses of free text questions accompanying each item of the instrument. (iii) Internal structure was assessed by exploratory factor analysis (EFA) and inter-rater reliability by generalizability analysis. Results: Content analysis was reasonably supported by the theoretical foundation and the VP expert team. The think-aloud studies and analysis of free text comments supported the validity of the instrument. In the EFA, using 2547 student evaluations of a total of 78 VPs, a three-factor model showed a reasonable fit with the data. At least 200 student responses are needed to obtain a reliable evaluation of a VP on all three factors. Conclusion: The instrument has the potential to provide valid information about VP design, provided that many responses per VP are available.
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Accurate three-dimensional (3D) models of lumbar vertebrae are required for image-based 3D kinematics analysis. MRI or CT datasets are frequently used to derive 3D models but have the disadvantages that they are expensive, time-consuming or involving ionizing radiation (e.g., CT acquisition). In this chapter, we present an alternative technique that can reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image and a statistical shape model. Cadaveric studies are conducted to verify the reconstruction accuracy by comparing the surface models reconstructed from a single lateral fluoroscopic image to the ground truth data from 3D CT segmentation. A mean reconstruction error between 0.7 and 1.4 mm was found.
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Automated identification of vertebrae from X-ray image(s) is an important step for various medical image computing tasks such as 2D/3D rigid and non-rigid registration. In this chapter we present a graphical model-based solution for automated vertebra identification from X-ray image(s). Our solution does not ask for a training process using training data and has the capability to automatically determine the number of vertebrae visible in the image(s). This is achieved by combining a graphical model-based maximum a posterior probability (MAP) estimate with a mean-shift based clustering. Experiments conducted on simulated X-ray images as well as on a low-dose low quality X-ray spinal image of a scoliotic patient verified its performance.
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Periacetabular osteotomy (PAO) is an effective approach for surgical treatment of hip dysplasia. The aim of PAO is to increase acetabular coverage of the femoral head and to reduce contact pressures by reorienting the acetabulum fragment after PAO. The success of PAO significantly depends on the surgeon’s experience. Previously, we have developed a computer-assisted planning and navigation system for PAO, which allows for not only quantifying the 3D hip morphology for a computer-assisted diagnosis of hip dysplasia but also a virtual PAO surgical planning and simulation. In this paper, based on this previously developed PAO planning and navigation system, we developed a 3D finite element (FE) model to investigate the optimal acetabulum reorientation after PAO. Our experimental results showed that an optimal position of the acetabulum can be achieved that maximizes contact area and at the same time minimizes peak contact pressure in pelvic and femoral cartilages. In conclusion, our computer-assisted planning and navigation system with FE modeling can be a promising tool to determine the optimal PAO planning strategy.
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This paper proposed an automated 3D lumbar intervertebral disc (IVD) segmentation strategy from MRI data. Starting from two user supplied landmarks, the geometrical parameters of all lumbar vertebral bodies and intervertebral discs are automatically extracted from a mid-sagittal slice using a graphical model based approach. After that, a three-dimensional (3D) variable-radius soft tube model of the lumbar spine column is built to guide the 3D disc segmentation. The disc segmentation is achieved as a multi-kernel diffeomorphic registration between a 3D template of the disc and the observed MRI data. Experiments on 15 patient data sets showed the robustness and the accuracy of the proposed algorithm.
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Purpose Malposition of the acetabular component in total hip arthroplasty (THA) is a common surgical problem that can lead to hip dislocation, reduced range of motion and may result in early loosening. The aim of this study is to validate the accuracy and reproducibility of a single x-ray image based 2D/3D reconstruction technique in determining cup inclination and anteversion against two different computer tomography (CT)-based measurement techniques. Methods Cup anteversion and inclination of 20 patients after cementless primary THA was measured on standard anteroposterior (AP) radiographs with the help of the single x-ray 2D/3D reconstruction program and compared with two different 3D CT-based analyses [Ground Truth (GT) and MeVis (MV) reconstruction model]. Results The measurements from the single x-ray 2D/3D reconstruction technique were strongly correlated with both types of CT image-processing protocols for both cup inclination [R²=0.69 (GT); R²=0.59 (MV)] and anteversion [R²=0.89 (GT); R²=0.80 (MV)]. Conclusions The single x-ray image based 2D/3D reconstruction technique is a feasible method to assess cup position on postoperative x-rays. CTscans remain the golden standard for a more complex biomechanical evaluation when a lower tolerance limit (+/-2 degrees) is required.
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This study evaluated the feasibility of documenting patterned injury using three dimensions and true colour photography without complex 3D surface documentation methods. This method is based on a generated 3D surface model using radiologic slice images (CT) while the colour information is derived from photographs taken with commercially available cameras. The external patterned injuries were documented in 16 cases using digital photography as well as highly precise photogrammetry-supported 3D structured light scanning. The internal findings of these deceased were recorded using CT and MRI. For registration of the internal with the external data, two different types of radiographic markers were used and compared. The 3D surface model generated from CT slice images was linked with the photographs, and thereby digital true-colour 3D models of the patterned injuries could be created (Image projection onto CT/IprojeCT). In addition, these external models were merged with the models of the somatic interior. We demonstrated that 3D documentation and visualization of external injury findings by integration of digital photography in CT/MRI data sets is suitable for the 3D documentation of individual patterned injuries to a body. Nevertheless, this documentation method is not a substitution for photogrammetry and surface scanning, especially when the entire bodily surface is to be recorded in three dimensions including all external findings, and when precise data is required for comparing highly detailed injury features with the injury-inflicting tool.
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67P/Churyumov-Gerasimenko (67P) is a Jupiter-family comet and the object of investigation of the European Space Agency mission Rosetta. This report presents the first full 3D simulation results of 67P’s neutral gas coma. In this study we include results from a direct simulation Monte Carlo method, a hydrodynamic code, and a purely geometric calculation which computes the total illuminated surface area on the nucleus. All models include the triangulated 3D shape model of 67P as well as realistic illumination and shadowing conditions. The basic concept is the assumption that these illumination conditions on the nucleus are the main driver for the gas activity of the comet. As a consequence, the total production rate of 67P varies as a function of solar insolation. The best agreement between the model and the data is achieved when gas fluxes on the night side are in the range of 7% to 10% of the maximum flux, accounting for contributions from the most volatile components. To validate the output of our numerical simulations we compare the results of all three models to in situ gas number density measurements from the ROSINA COPS instrument. We are able to reproduce the overall features of these local neutral number density measurements of ROSINA COPS for the time period between early August 2014 and January 1 2015 with all three models. Some details in the measurements are not reproduced and warrant further investigation and refinement of the models. However, the overall assumption that illumination conditions on the nucleus are at least an important driver of the gas activity is validated by the models. According to our simulation results we find the total production rate of 67P to be constant between August and November 2014 with a value of about 1 × 10²⁶ molecules s⁻¹.
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This paper proposed an automated three-dimensional (3D) lumbar intervertebral disc (IVD) segmentation strategy from Magnetic Resonance Imaging (MRI) data. Starting from two user supplied landmarks, the geometrical parameters of all lumbar vertebral bodies and intervertebral discs are automatically extracted from a mid-sagittal slice using a graphical model based template matching approach. Based on the estimated two-dimensional (2D) geometrical parameters, a 3D variable-radius soft tube model of the lumbar spine column is built by model fitting to the 3D data volume. Taking the geometrical information from the 3D lumbar spine column as constraints and segmentation initialization, the disc segmentation is achieved by a multi-kernel diffeomorphic registration between a 3D template of the disc and the observed MRI data. Experiments on 15 patient data sets showed the robustness and the accuracy of the proposed algorithm.