52 resultados para Computer aided analysis, Machine vision, Video surveillance


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PURPOSE To evaluate technical complications and failures of zirconia-based fixed prostheses supported by implants. MATERIALS AND METHODS Consecutive patients received zirconia-based single crowns (SCs) and fixed dental prostheses (FDPs) on implants in a private clinical setting between 2005 and 2010. One dentist performed all surgical and prosthetic procedures, and one master technician performed and coordinated all laboratory procedures. One-piece computer-aided design/ computer-assisted manufacture technology was used to fabricate abutments and frameworks, which were directly connected at the implant level, where possible. All patients were involved in a recall maintenance program and were finally reviewed in 2012. Data on framework fractures, chipping of veneering ceramics, and other technical complications were recorded. The primary endpoint was failure of the prostheses, ie, the need for a complete remake. A life table analysis was calculated. RESULTS A total of 289 implants supported 193 zirconia-based prostheses (120 SCs and 73 FDPs) in 127 patients (51 men, 76 women; average age: 62.5 ± 13.4 years) who were reviewed in 2012. Twenty-five (13%) prostheses were cemented on 44 zirconia abutments and 168 (87%) prostheses were screw-retained directly at the implant level. Fracture of 3 frameworks (1 SC, 2 FDPs) was recorded, and significant chipping resulted in the remake of 3 prostheses (1 SC, 2 FDPs). The 7-year cumulative survival rate was 96.4% ± 1.99%. Minor complications comprised 5 loose screws (these were retightened), small chips associated with 3 prostheses (these were polished), and dislodgement of 3 prostheses (these were recemented). Overall, 176 prostheses remained free of technical problems. CONCLUSIONS Zirconia-based prostheses screwed directly to implants are clinically successful in the short and medium term.

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Over the last decade, a plethora of computer-aided diagnosis (CAD) systems have been proposed aiming to improve the accuracy of the physicians in the diagnosis of interstitial lung diseases (ILD). In this study, we propose a scheme for the classification of HRCT image patches with ILD abnormalities as a basic component towards the quantification of the various ILD patterns in the lung. The feature extraction method relies on local spectral analysis using a DCT-based filter bank. After convolving the image with the filter bank, q-quantiles are computed for describing the distribution of local frequencies that characterize image texture. Then, the gray-level histogram values of the original image are added forming the final feature vector. The classification of the already described patches is done by a random forest (RF) classifier. The experimental results prove the superior performance and efficiency of the proposed approach compared against the state-of-the-art.

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In this work we solve the uncalibrated photometric stereo problem with lights placed near the scene. We investigate different image formation models and find the one that best fits our observations. Although the devised model is more complex than its far-light counterpart, we show that under a global linear ambiguity the reconstruction is possible up to a rotation and scaling, which can be easily fixed. We also propose a solution for reconstructing the normal map, the albedo, the light positions and the light intensities of a scene given only a sequence of near-light images. This is done in an alternating minimization framework which first estimates both the normals and the albedo, and then the light positions and intensities. We validate our method on real world experiments and show that a near-light model leads to a significant improvement in the surface reconstruction compared to the classic distant illumination case.

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In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

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The purpose of the present study was to investigate whether serous fluids, blood, cerebrospinal fluid (CSF), and putrefied CSF can be characterized and differentiated in synthetically calculated magnetic resonance (MR) images based on their quantitative T 1, T 2, and proton density (PD) values. Images from 55 postmortem short axis cardiac and 31 axial brain 1.5-T MR examinations were quantified using a quantification sequence. Serous fluids, fluid blood, sedimented blood, blood clots, CSF, and putrefied CSF were analyzed for their mean T 1, T 2, and PD values. Body core temperature was measured during the MRI scans. The fluid-specific quantitative values were related to the body core temperature. Equations to correct for temperature differences were generated. In a 3D plot as well as in statistical analysis, the quantitative T 1, T 2 and PD values of serous fluids, fluid blood, sedimented blood, blood clots, CSF, and putrefied CSF could be well differentiated from each other. The quantitative T 1 and T 2 values were temperature-dependent. Correction of quantitative values to a temperature of 37 °C resulted in significantly better discrimination between all investigated fluid mediums. We conclude that postmortem 1.5-T MR quantification is feasible to discriminate between blood, serous fluids, CSF, and putrefied CSF. This finding provides a basis for the computer-aided diagnosis and detection of fluids and hemorrhages.

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BACKGROUND Recent technical development allows the digital manufacturing of monolithic reconstructions with high-performance materials. For implant-supported crowns, the fixation requires an abutment design onto which the reconstruction can be bonded. PURPOSE The aim of this laboratory investigation was to analyze stiffness, strength, and failure modes of implant-supported, computer-assisted design and computer-aided manufacturing (CAD/CAM)-generated resin nano ceramic (RNC) crowns bonded to three different titanium abutments. MATERIALS AND METHODS Eighteen monolithic RNC crowns were produced and loaded in a universal testing machine under quasi-static condition according to DIN ISO 14801. With regard to the type of titanium abutment, three groups were defined: (1) prefabricated cementable standard; (2) CAD/CAM-constructed individualized; and (3) novel prefabricated bonding base. Stiffness and strength were measured and analyzed statistically with Wilcoxon rank sum test. Sections of the specimens were examined microscopically. RESULTS Stiffness demonstrated high stability for all specimens loaded in the physiological loading range with means and standard deviations of 1,579 ± 120 N/mm (group A), 1,733 ± 89 N/mm (group B), and 1,704 ± 162 N/mm (group C). Mean strength of the novel prefabricated bonding base (group C) was 17% lower than of the two other groups. Plastic deformations were detectable for all implant-abutment crown connections. CONCLUSIONS Monolithic implant crowns made of RNC seem to represent a feasible and stable prosthetic construction under laboratory testing conditions with strength higher than the average occlusal force, independent of the different abutment designs used in this investigation.

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PURPOSE The study aims to evaluate three-dimensionally (3D) the accuracy of implant impressions using a new resin splinting material, "Smart Dentin Replacement" (SDR). MATERIALS AND METHODS A titanium model of an edentulous mandible with six implant analogues was used as a master model and its dimensions measured with a coordinate measuring machine. Before the total 60 impressions were taken (open tray, screw-retained abutments, vinyl polysiloxane), they were divided in four groups: A (test): copings pick-up splinted with dental floss and fotopolymerizing SDR; B (test): see A, additionally sectioned and splinted again with SDR; C (control): copings pick-up splinted with dental floss and autopolymerizing Duralay® (Reliance Dental Mfg. Co., Alsip, IL, USA) acrylic resin; and D (control): see C, additionally sectioned and splinted again with Duralay. The impressions were measured directly with an optomechanical coordinate measuring machine and analyzed with a computer-aided design (CAD) geometric modeling software. The Wilcoxon matched-pair signed-rank test was used to compare groups. RESULTS While there was no difference (p = .430) between the mean 3D deviations of the test groups A (17.5 μm) and B (17.4 μm), they both showed statistically significant differences (p < .003) compared with both control groups (C 25.0 μm, D 19.1 μm). CONCLUSIONS Conventional impression techniques for edentulous jaws with multiple implants are highly accurate using the new fotopolymerizing splinting material SDR. Sectioning and rejoining of the SDR splinting had no impact on the impression accuracy.