60 resultados para Data detection

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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This paper presents an automated solution for precise detection of fiducial screws from three-dimensional (3D) Computerized Tomography (CT)/Digital Volume Tomography (DVT) data for image-guided ENT surgery. Unlike previously published solutions, we regard the detection of the fiducial screws from the CT/DVT volume data as a pose estimation problem. We thus developed a model-based solution. Starting from a user-supplied initialization, our solution detects the fiducial screws by iteratively matching a computer aided design (CAD) model of the fiducial screw to features extracted from the CT/DVT data. We validated our solution on one conventional CT dataset and on five DVT volume datasets, resulting in a total detection of 24 fiducial screws. Our experimental results indicate that the proposed solution achieves much higher reproducibility and precision than the manual detection. Further comparison shows that the proposed solution produces better results on the DVT dataset than on the conventional CT dataset.

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In this paper, we propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. To detect landmarks, we estimate the displacements from some randomly sampled image patches to the (unknown) landmark positions, and then we integrate these predictions via a voting scheme. Our key contribution is a new algorithm for estimating these displacements. Different from other methods where each image patch independently predicts its displacement, we jointly estimate the displacements from all patches together in a data driven way, by considering not only the training data but also geometric constraints on the test image. The displacements estimation is formulated as a convex optimization problem that can be solved efficiently. Finally, we use the sparse shape composition model as the a priori information to regularize the landmark positions and thus generate the segmented shape contour. We validate our method on X-ray image datasets of three different anatomical structures: complete femur, proximal femur and pelvis. Experiments show that our method is accurate and robust in landmark detection, and, combined with the shape model, gives a better or comparable performance in shape segmentation compared to state-of-the art methods. Finally, a preliminary study using CT data shows the extensibility of our method to 3D data.

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Background Protein-energy-malnutrition (PEM) is common in people with end stage kidney disease (ESKD) undergoing maintenance haemodialysis (MHD) and correlates strongly with mortality. To this day, there is no gold standard for detecting PEM in patients on MHD. Aim of Study The aim of this study was to evaluate if Nutritional Risk Screening 2002 (NRS-2002), handgrip strength measurement, mid-upper arm muscle area (MUAMA), triceps skin fold measurement (TSF), serum albumin, normalised protein catabolic rate (nPCR), Kt/V and eKt/V, dry body weight, body mass index (BMI), age and time since start on MHD are relevant for assessing PEM in patients on MHD. Methods The predictive value of the selected parameters on mortality and mortality or weight loss of more than 5% was assessed. Quantitative data analysis of the 12 parameters in the same patients on MHD in autumn 2009 (n = 64) and spring 2011 (n = 40) with paired statistical analysis and multivariate logistic regression analysis was performed. Results Paired data analysis showed significant reduction of dry body weight, BMI and nPCR. Kt/Vtot did not change, eKt/v and hand grip strength measurements were significantly higher in spring 2011. No changes were detected in TSF, serum albumin, NRS-2002 and MUAMA. Serum albumin was shown to be the only predictor of death and of the combined endpoint “death or weight loss of more than 5%”. Conclusion We now screen patients biannually for serum albumin, nPCR, Kt/V, handgrip measurement of the shunt-free arm, dry body weight, age and time since initiation of MHD.

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Current methods for detection of copy number variants (CNV) and aberrations (CNA) from targeted sequencing data are based on the depth of coverage of captured exons. Accurate CNA determination is complicated by uneven genomic distribution and non-uniform capture efficiency of targeted exons. Here we present CopywriteR, which eludes these problems by exploiting 'off-target' sequence reads. CopywriteR allows for extracting uniformly distributed copy number information, can be used without reference, and can be applied to sequencing data obtained from various techniques including chromatin immunoprecipitation and target enrichment on small gene panels. CopywriteR outperforms existing methods and constitutes a widely applicable alternative to available tools.

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We have investigated the use of hierarchical clustering of flow cytometry data to classify samples of conventional central chondrosarcoma, a malignant cartilage forming tumor of uncertain cellular origin, according to similarities with surface marker profiles of several known cell types. Human primary chondrosarcoma cells, articular chondrocytes, mesenchymal stem cells, fibroblasts, and a panel of tumor cell lines from chondrocytic or epithelial origin were clustered based on the expression profile of eleven surface markers. For clustering, eight hierarchical clustering algorithms, three distance metrics, as well as several approaches for data preprocessing, including multivariate outlier detection, logarithmic transformation, and z-score normalization, were systematically evaluated. By selecting clustering approaches shown to give reproducible results for cluster recovery of known cell types, primary conventional central chondrosacoma cells could be grouped in two main clusters with distinctive marker expression signatures: one group clustering together with mesenchymal stem cells (CD49b-high/CD10-low/CD221-high) and a second group clustering close to fibroblasts (CD49b-low/CD10-high/CD221-low). Hierarchical clustering also revealed substantial differences between primary conventional central chondrosarcoma cells and established chondrosarcoma cell lines, with the latter not only segregating apart from primary tumor cells and normal tissue cells, but clustering together with cell lines from epithelial lineage. Our study provides a foundation for the use of hierarchical clustering applied to flow cytometry data as a powerful tool to classify samples according to marker expression patterns, which could lead to uncover new cancer subtypes.

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The characteristic features of Whipple's disease include abdominal pain, diarrhoea, wasting, and arthralgias, with the causative agent, Tropheryma whipplei, being detected mainly in intestinal biopsies. PCR technology has led to the identification of T. whipplei in specimens from various other locations, including the central nervous system and the heart. T. whipplei is now recognized as one of the causes of culture-negative endocarditis, and endocarditis can be the only manifestation of the infection with T. whipplei. Although it is considered a rare disease, the true incidence of endocarditis due to T. whipplei is not clearly established. With the increasing use of molecular methods, it is likely that T. whipplei will be more frequently identified. Questions also remain about the genetic variability of T. whipplei strains, optimal diagnostic procedures and therapeutic options. In the present study, we provide clinical data on four new patients with documented endocarditis due to T. whipplei in the context of the available published literature. There was no clinical involvement of the gastrointestinal tract. Genetic analysis of the T. whipplei strains with DNA isolated from the excised heart valves revealed little to no genetic variability. In a selected case, we describe acridine orange staining for early detection of the disease, prompting early adaptation of the antibiotic therapy. We provide long-term follow-up data on the patients. In our hands, an initial 2-week course of intravenous antibiotics followed by cotrimoxazole for at least 1 year was a suitable treatment option for T. whipplei endocarditis.

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Robust and accurate identification of intervertebral discs from low resolution, sparse MRI scans is essential for the automated scan planning of the MRI spine scan. This paper presents a graphical model based solution for the detection of both the positions and orientations of intervertebral discs from low resolution, sparse MRI scans. Compared with the existing graphical model based methods, the proposed method does not need a training process using training data and it also has the capability to automatically determine the number of vertebrae visible in the image. Experiments on 25 low resolution, sparse spine MRI data sets verified its performance.

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Cardiogoniometry (CGM), a spatiotemporal electrocardiologic 5-lead method with automated analysis, may be useful in primary healthcare for detecting coronary artery disease (CAD) at rest. Our aim was to systematically develop a stenosis-specific parameter set for global CAD detection. In 793 consecutively admitted patients with presumed non-acute CAD, CGM data were collected prior to elective coronary angiography and analyzed retrospectively. 658 patients fulfilled the inclusion criteria, 405 had CAD verified by coronary angiography; the 253 patients with normal coronary angiograms served as the non-CAD controls. Study patients--matched for age, BMI, and gender--were angiographically assigned to 8 stenosis-specific CAD categories or to the controls. One CGM parameter possessing significance (P < .05) and the best diagnostic accuracy was matched to one CAD category. The area under the ROC curve was .80 (global CAD versus controls). A set containing 8 stenosis-specific CGM parameters described variability of R vectors and R-T angles, spatial position and potential distribution of R/T vectors, and ST/T segment alterations. Our parameter set systematically combines CAD categories into an algorithm that detects CAD globally. Prospective validation in clinical studies is ongoing.

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Conventional MRI may still be an inaccurate method for the non-invasive detection of a microadenoma in adrenocorticotropin (ACTH)-dependent Cushing's syndrome (CS). Bilateral inferior petrosal sinus sampling (BIPSS) with ovine corticotropin-releasing hormone (oCRH) stimulation is an invasive, but accurate, intervention in the diagnostic armamentarium surrounding CS. Until now, there is a continuous controversial debate regarding lateralization data in detecting a microadenoma. Using BIPSS, we evaluated whether a highly selective placement of microcatheters without diversion of venous outflow might improve detection of pituitary microadenoma.

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Local to regional climate anomalies are to a large extent determined by the state of the atmospheric circulation. The knowledge of large-scale sea level pressure (SLP) variations in former times is therefore crucial when addressing past climate changes across Europe and the Mediterranean. However, currently available SLP reconstructions lack data from the ocean, particularly in the pre-1850 period. Here we present a new statistically-derived 5° × 5° resolved gridded seasonal SLP dataset covering the eastern North Atlantic, Europe and the Mediterranean area (40°W–50°E; 20°N–70°N) back to 1750 using terrestrial instrumental pressure series and marine wind information from ship logbooks. For the period 1750–1850, the new SLP reconstruction provides a more accurate representation of the strength of the winter westerlies as well as the location and variability of the Azores High than currently available multiproxy pressure field reconstructions. These findings strongly support the potential of ship logbooks as an important source to determine past circulation variations especially for the pre-1850 period. This new dataset can be further used for dynamical studies relating large-scale atmospheric circulation to temperature and precipitation variability over the Mediterranean and Eurasia, for the comparison with outputs from GCMs as well as for detection and attribution studies.

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An automated algorithm for detection of the acetabular rim was developed. Accuracy of the algorithm was validated in a sawbone study and compared against manually conducted digitization attempts, which were established as the ground truth. The latter proved to be reliable and reproducible, demonstrated by almost perfect intra- and interobserver reliability. Validation of the automated algorithm showed no significant difference compared to the manually acquired data in terms of detected version and inclination. Automated detection of the acetabular rim contour and the spatial orientation of the acetabular opening plane can be accurately achieved with this algorithm.

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Postmortem imaging has gained prominence in the field of forensic pathology. Even with experience in this procedure, difficulties arise in evaluating pathologies of the postmortem lung. The effect of postmortem ventilation with applied pressures of 10, 20, 30 and 40mbar was evaluated in 10 corpses using simultaneous postmortem computed tomography (pmCT) scans. Ventilation was performed via a continuous positive airway pressure mask (n=5), an endotracheal tube (n=4) and a laryngeal mask (n=1) using a portable home care ventilator. The lung volumes were measured and evaluated by a segmentation technique based on reconstructed CT data. The resulting changes to the lungs were analyzed. Postmortem ventilation at 40mbar induced a significant (p<0.05) unfolding of the lungs, with a mean volume increase of 1.32l. Small pathologies of the lung such as scarring and pulmonary nodules as well as emphysema were revealed, while inner livores were reduced. Even though lower ventilation pressures resulted in a significant (p<0.05) volume increase, pathologies were best evaluated when a pressure of 40mbar was applied, due to the greater reduction of the inner livores. With the ventilation-induced expansion of the lungs, a decrease in the heart diameter and gaseous distension of the stomach was recognized. In conclusion, postmortem ventilation is a feasible method for improving evaluation of the lungs and detection of small lung pathologies. This is because of the volume increase in the air-filled portions of the lung and reduced appearance of inner livores.

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We tested the use of multiplex real-time PCR for detection and quantification of Campylobacter jejuni and Campylobacter coli on broiler carcass neck skin samples collected during 2008 from slaughterhouses in Switzerland. Results from an established TaqMan assay based on two different targets (hipO and ceuE for C. jejuni and C. coli, respectively) were corroborated with data from a newly developed assay based on a single-nucleotide polymorphism in the fusA gene, which allows differentiation between C. jejuni and C. coli. Both multiplex real-time PCRs were applied simultaneously for direct detection, differentiation, and quantification of Campylobacter from 351 neck skin samples and compared with culture methods. There was good correlation in detection and enumeration between real-time PCR results and quantitative culture, with real-time PCR being more sensitive. Overall, 251 (71.5%) of the samples were PCR positive for Campylobacter, with 211 (60.1%) in the hipO-ceuE assays, 244 (69.5%) in the fusA assay, and 204 (58.1%) of them being positive in both PCR assays. Thus, the fusA assay was similarly sensitive to the enrichment culture (72.4% positive); however, it is faster and allows for quantification. In addition, real-time PCR allowed for species differentiation; roughly 60% of positive samples contained C. jejuni, less than 10% C. coli, and more than 30% contained both species. Real-time PCR proved to be a suitable method for direct detection, quantification, and differentiation of Campylobacter from carcasses, and could permit time-efficient surveillance of these zoonotic agents.