938 resultados para quantitative image analysis
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The objective of this work was to determine the contents of methylxanthines, caffeine and theobromine, and phenolic compounds, chlorogenic and caffeic acids, in 51 mate progenies (half-sib families) and estimate the heritability of genetic parameters. Mate progenies were from five Brazilian municipalities: Pinhão, Ivaí, Barão de Cotegipe, Quedas do Iguaçu, and Cascavel. The progenies were grown in the Ivaí locality. The contents of the compounds were obtained by high performance liquid chromatography (HPLC). The estimation of genetic parameters by the restricted maximum likelihood (REML) and the prediction of genotypic values via best linear unbiased prediction (BLUP) were obtained by the Selegen - REML/BLUP software. Caffeine (0.248-1.663%) and theobromine (0.106-0.807%) contents were significantly different (p<0.05) depending on the region of origin, with high individual heritability (ĥ²>0.5). The two different progeny groups determined for chlorogenic (1.365-2.281%) and caffeic (0.027-0.037%) acid contents were not significantly different (p<0.05) depending on the locality of origin. Individual heritability values were low to medium for chlorogenic (ĥ²<0.4) and caffeic acid (ĥ²<0.3). The content of the compounds and the values of genetic parameters could support breeding programs for mate.
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The major objective of this project is to evaluate image analysis for characterizing air voids in Portland cement contract (PCC) and asphalt concrete (AC) and aggregate gradation in asphalt concrete. Phase 1 of this project has concentrated on evaluation and refinement of sample preparation techniques, evaluation of methods and instruments for conducting image analysis, and finally, analysis and comparison of a select portion of samples. Preliminary results suggest a strong correlation between the results obtained from the linear traverse method and image analysis methods for determining percent air voids in concrete. Preliminary work with asphalt samples has shown that damage caused by a high vacuum of the conventional scanning electron microscope (SEM) may too disruptive. Alternative solutions have been explored, including confocal microscopy and low vacuum electron microscopy. Additionally, a conventional high vacuum SEM operating at a marginal operating vacuum may suffice.
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The topic of this thesis is studying how lesions in retina caused by diabetic retinopathy can be detected from color fundus images by using machine vision methods. Methods for equalizing uneven illumination in fundus images, detecting regions of poor image quality due toinadequate illumination, and recognizing abnormal lesions were developed duringthe work. The developed methods exploit mainly the color information and simpleshape features to detect lesions. In addition, a graphical tool for collecting lesion data was developed. The tool was used by an ophthalmologist who marked lesions in the images to help method development and evaluation. The tool is a general purpose one, and thus it is possible to reuse the tool in similar projects.The developed methods were tested with a separate test set of 128 color fundus images. From test results it was calculated how accurately methods classify abnormal funduses as abnormal (sensitivity) and healthy funduses as normal (specificity). The sensitivity values were 92% for hemorrhages, 73% for red small dots (microaneurysms and small hemorrhages), and 77% for exudates (hard and soft exudates). The specificity values were 75% for hemorrhages, 70% for red small dots, and 50% for exudates. Thus, the developed methods detected hemorrhages accurately and microaneurysms and exudates moderately.
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The integration of information which can be gained from accessory [i.e. age (t)] and rock-forming minerals [i.e. temperature (T) and pressure (P)] requires a more profound understanding of the equilibration kinetics during metamorphic processes. This paper presents an approach comparing conventional P-T estimate from equilibrated assemblages of rock-forming minerals with temperature data derived from yttrium-garnet-monazite (YGM) and yttrium-garnet-xenotime (YGX) geothermometry. Such a comparison provides an initial indication on differences between equilibration of major and trace elements. Regarding this purpose, two migmatites, two polycyclic and one monocyclic gneiss from the Central Alps (Switzerland, northern Italy) were investigated. While the polycyclic samples exhibit trace-element equilibration between monazite and garnet grains assigned to the same metamorphic event, there are relics of monazite and garnet obviously surviving independent of their textural position. These observations suggest that surface processes dominate transport processes during equilibration of those samples. The monocyclic gneiss, on the contrary, displays rare isolated monazite with equilibration of all elements, despite comparably large transport distances. With a nearly linear crystal-size distribution of the garnet grain population, growth kinetics, related to the major elements, were likely surface-controlled in this sample. In contrast to these completely equilibrated examples, the migmatites indicate disequilibrium between garnet and monazite with a change in REE patterns on garnet transects. The cause for this disequilibrium may be related to a potential disequilibrium initiated by a changing bulk chemistry during melt segregation. While migmatite environments are expected to support high transport rates (i.e. high temperatures and melt presence), the evolution of equilibration in migmatites is additionaly related to change in chemistry. As a key finding, surface-controlled equilibration kinetics seem to dominate transport-controlled processes in the investigated samples. This may be decisive information towards the understanding of age data derived from monazite.
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Tärkeä tehtävä ympäristön tarkkailussa on arvioida ympäristön nykyinen tila ja ihmisen siihen aiheuttamat muutokset sekä analysoida ja etsiä näiden yhtenäiset suhteet. Ympäristön muuttumista voidaan hallita keräämällä ja analysoimalla tietoa. Tässä diplomityössä on tutkittu vesikasvillisuudessa hai vainuja muutoksia käyttäen etäältä hankittua mittausdataa ja kuvan analysointimenetelmiä. Ympäristön tarkkailuun on käytetty Suomen suurimmasta järvestä Saimaasta vuosina 1996 ja 1999 otettuja ilmakuvia. Ensimmäinen kuva-analyysin vaihe on geometrinen korjaus, jonka tarkoituksena on kohdistaa ja suhteuttaa otetut kuvat samaan koordinaattijärjestelmään. Toinen vaihe on kohdistaa vastaavat paikalliset alueet ja tunnistaa kasvillisuuden muuttuminen. Kasvillisuuden tunnistamiseen on käytetty erilaisia lähestymistapoja sisältäen valvottuja ja valvomattomia tunnistustapoja. Tutkimuksessa käytettiin aitoa, kohinoista mittausdataa, minkä perusteella tehdyt kokeet antoivat hyviä tuloksia tutkimuksen onnistumisesta.
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Laser diffraction (LD) and static image analysis (SIA) of rectangular particles [United States Pharmacopeia, USP30-NF25, General Chapter <776>, Optical Miroscopy.] have been systematically studied. To rule out sample dispersion and particle orientation as the root cause of differences in size distribution profiles, we immobilize powder samples on a glass plate by means of a dry disperser. For a defined region of the glass plate, we measure the diffraction pattern as induced by the dispersed particles, and the 2D dimensions of the individual particles using LD and optical microscopy, respectively. We demonstrate a correlation between LD and SIA, with the scattering intensity of the individual particles as the dominant factor. In theory, the scattering intensity is related to the square of the projected area of both spherical and rectangular particles. In traditional LD the size distribution profile is dominated by the maximum projected area of the particles (A). The diffraction diameters of a rectangular particle with length L and breadth B as measured by the LD instrument approximately correspond to spheres of diameter ØL and ØB respectively. Differences in the scattering intensity between spherical and rectangular particles suggest that the contribution made to the overall LD volume probability distribution by each rectangular particle is proportional to A2/L and A2/B. Accordingly, for rectangular particles the scattering intensity weighted diffraction diameter (SIWDD) explains an overestimation of their shortest dimension and an underestimation of their longest dimension. This study analyzes various samples of particles whose length ranges from approximately 10 to 1000 μm. The correlation we demonstrate between LD and SIA can be used to improve validation of LD methods based on SIA data for a variety of pharmaceutical powders all with a different rectangular particle size and shape.
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A total of over 200 different samples of bark and wood of Silver birch, Norway spruce and Scots pine were analysed. Samples were taken from several areas in western Finland, some with known sources of atmospheric heavy metal emission (Harjavalta, Ykspihlaja). Also analytical data for pine needles from some sites are reported. The chemical analyses were performed by thick-target particle-induced X-ray emission (PIXE) spectrometry after preconcentration by dry ashing of samples at 550oC. The following elements were quantified in most of the samples: P, S, K, Ca, Mn, Fe, Ni, Cu, Zn, Rb, Sr, Cd, Ba and Pb. The ash percentage and the chemical composition of ashes of different wood materials were also obtained, as dry ashing was used in the analytical procedure. The variations in elemental concentrations in wood and bark of an individual tree, expressed as RSDs, were mostly in the range 10 – 20 %. For several trees of the same species sampled from small areas (< 1 ha), the variations in elemental concentrations were surprisingly high (RSDs 20 – 50 %). In the vicinity of metal plants, effects of strong atmospheric heavy metal pollution (pollution factor above 100) were observed in pine bark. The increase of heavy metal content in wood samples from the same sites was quite small. Elemental concentrations in ashes of bark and wood, from areas with no local source of atmospheric pollution, were relatively uniform. Based on this observation an alternative way of demonstrating atmospheric pollution of tree bark is discussed.
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UNLABELLED: In vivo transcriptional analyses of microbial pathogens are often hampered by low proportions of pathogen biomass in host organs, hindering the coverage of full pathogen transcriptome. We aimed to address the transcriptome profiles of Candida albicans, the most prevalent fungal pathogen in systemically infected immunocompromised patients, during systemic infection in different hosts. We developed a strategy for high-resolution quantitative analysis of the C. albicans transcriptome directly from early and late stages of systemic infection in two different host models, mouse and the insect Galleria mellonella. Our results show that transcriptome sequencing (RNA-seq) libraries were enriched for fungal transcripts up to 1,600-fold using biotinylated bait probes to capture C. albicans sequences. This enrichment biased the read counts of only ~3% of the genes, which can be identified and removed based on a priori criteria. This allowed an unprecedented resolution of C. albicans transcriptome in vivo, with detection of over 86% of its genes. The transcriptional response of the fungus was surprisingly similar during infection of the two hosts and at the two time points, although some host- and time point-specific genes could be identified. Genes that were highly induced during infection were involved, for instance, in stress response, adhesion, iron acquisition, and biofilm formation. Of the in vivo-regulated genes, 10% are still of unknown function, and their future study will be of great interest. The fungal RNA enrichment procedure used here will help a better characterization of the C. albicans response in infected hosts and may be applied to other microbial pathogens. IMPORTANCE: Understanding the mechanisms utilized by pathogens to infect and cause disease in their hosts is crucial for rational drug development. Transcriptomic studies may help investigations of these mechanisms by determining which genes are expressed specifically during infection. This task has been difficult so far, since the proportion of microbial biomass in infected tissues is often extremely low, thus limiting the depth of sequencing and comprehensive transcriptome analysis. Here, we adapted a technology to capture and enrich C. albicans RNA, which was next used for deep RNA sequencing directly from infected tissues from two different host organisms. The high-resolution transcriptome revealed a large number of genes that were so far unknown to participate in infection, which will likely constitute a focus of study in the future. More importantly, this method may be adapted to perform transcript profiling of any other microbes during host infection or colonization.
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OBJECTIVE: To evaluate lung fissures completeness, post-treatment radiological response and quantitative CT analysis (QCTA) in a population of severe emphysematous patients submitted to endobronchial valves (EBV) implantation. MATERIALS AND METHODS: Multi-detectors CT exams of 29 patients were studied, using thin-section low dose protocol without contrast. Two radiologists retrospectively reviewed all images in consensus; fissures completeness was estimated in 5% increments and post-EBV radiological response (target lobe atelectasis/volume loss) was evaluated. QCTA was performed in pre and post-treatment scans using a fully automated software. RESULTS: CT response was present in 16/29 patients. In the negative CT response group, all 13 patients presented incomplete fissures, and mean oblique fissures completeness was 72.8%, against 88.3% in the other group. QCTA most significant results showed a reduced post-treatment total lung volume (LV) (mean 542 ml), reduced EBV-submitted LV (700 ml) and reduced emphysema volume (331.4 ml) in the positive response group, which also showed improved functional tests. CONCLUSION: EBV benefit is most likely in patients who have complete interlobar fissures and develop lobar atelectasis. In patients with no radiological response we observed a higher prevalence of incomplete fissures and a greater degree of incompleteness. The fully automated QCTA detected the post-treatment alterations, especially in the treated lung analysis.
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Postprint (published version)
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Coating and filler pigments have strong influence to the properties of the paper. Filler content can be even over 30 % and pigment content in coating is about 85-95 weight percent. The physical and chemical properties of the pigments are different and the knowledge of these properties is important for optimising of optical and printing properties of the paper. The size and shape of pigment particles can be measured by different analysers which can be based on sedimentation, laser diffraction, changes in electric field etc. In this master's thesis was researched particle properties especially by scanning electron microscope (SEM) and image analysis programs. Research included nine pigments with different particle size and shape. Pigments were analysed by two image analysis programs (INCA Feature and Poikki), Coulter LS230 (laser diffraction) and SediGraph 5100 (sedimentation). The results were compared to perceive the effect of particle shape to the performance of the analysers. Only image analysis programs gave parameters of the particle shape. One part of research was also the sample preparation for SEM. Individual particles should be separated and distinct in ideal sample. Analysing methods gave different results but results from image analysis programs corresponded even to sedimentation or to laser diffraction depending on the particle shape. Detailed analysis of the particle shape required high magnification in SEM, but measured parameters described very well the shape of the particles. Large particles (ecd~1 µm) could be used also in 3D-modelling which enabled the measurement of the thickness of the particles. Scanning electron microscope and image analysis programs were effective and multifunctional tools for particle analyses. Development and experience will devise the usability of analysing method in routine use.
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Multispectral images are becoming more common in the field of remote sensing, computer vision, and industrial applications. Due to the high accuracy of the multispectral information, it can be used as an important quality factor in the inspection of industrial products. Recently, the development on multispectral imaging systems and the computational analysis on the multispectral images have been the focus of a growing interest. In this thesis, three areas of multispectral image analysis are considered. First, a method for analyzing multispectral textured images was developed. The method is based on a spectral cooccurrence matrix, which contains information of the joint distribution of spectral classes in a spectral domain. Next, a procedure for estimating the illumination spectrum of the color images was developed. Proposed method can be used, for example, in color constancy, color correction, and in the content based search from color image databases. Finally, color filters for the optical pattern recognition were designed, and a prototype of a spectral vision system was constructed. The spectral vision system can be used to acquire a low dimensional component image set for the two dimensional spectral image reconstruction. The data obtained by the spectral vision system is small and therefore convenient for storing and transmitting a spectral image.
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Quickremovalofbiosolidsinaquaculturefacilities,andspeciallyinrecirculatingaquaculturesystems(RAS),isoneofthemostimportantstepinwastemanagement.Sedimentationdynamicsofbiosolidsinanaquaculturetankwilldeterminetheiraccumulationatthebottomofthetank.
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A qualitative spot-test and tandem quantitative analysis of dipyrone in the bulk drug and in pharmaceutical preparations is proposed. The formation of a reddish-violet color indicates a positive result. In sequence a quantitative procedure can be performed in the same flask. The quantitative results obtained were statistically compared with those obtained with the method indicated by the Brazilian Pharmacopoeia, using the Student's t and the F tests. Considering the concentration in a 100 µL aliquot, the qualitative visual limit of detection is about 5×10-6 g; instrumental LOD ≅ 1.4×10-4 mol L-1 ; LOQ ≅ 4.5×10-4 mol L-1.
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Diabetes is a rapidly increasing worldwide problem which is characterised by defective metabolism of glucose that causes long-term dysfunction and failure of various organs. The most common complication of diabetes is diabetic retinopathy (DR), which is one of the primary causes of blindness and visual impairment in adults. The rapid increase of diabetes pushes the limits of the current DR screening capabilities for which the digital imaging of the eye fundus (retinal imaging), and automatic or semi-automatic image analysis algorithms provide a potential solution. In this work, the use of colour in the detection of diabetic retinopathy is statistically studied using a supervised algorithm based on one-class classification and Gaussian mixture model estimation. The presented algorithm distinguishes a certain diabetic lesion type from all other possible objects in eye fundus images by only estimating the probability density function of that certain lesion type. For the training and ground truth estimation, the algorithm combines manual annotations of several experts for which the best practices were experimentally selected. By assessing the algorithm’s performance while conducting experiments with the colour space selection, both illuminance and colour correction, and background class information, the use of colour in the detection of diabetic retinopathy was quantitatively evaluated. Another contribution of this work is the benchmarking framework for eye fundus image analysis algorithms needed for the development of the automatic DR detection algorithms. The benchmarking framework provides guidelines on how to construct a benchmarking database that comprises true patient images, ground truth, and an evaluation protocol. The evaluation is based on the standard receiver operating characteristics analysis and it follows the medical practice in the decision making providing protocols for image- and pixel-based evaluations. During the work, two public medical image databases with ground truth were published: DIARETDB0 and DIARETDB1. The framework, DR databases and the final algorithm, are made public in the web to set the baseline results for automatic detection of diabetic retinopathy. Although deviating from the general context of the thesis, a simple and effective optic disc localisation method is presented. The optic disc localisation is discussed, since normal eye fundus structures are fundamental in the characterisation of DR.