910 resultados para Automated quantification


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The synapses in the cerebral cortex can be classified into two main types, Gray’s type I and type II, which correspond to asymmetric (mostly glutamatergic excitatory) and symmetric (inhibitory GABAergic) synapses, respectively. Hence, the quantification and identification of their different types and the proportions in which they are found, is extraordinarily important in terms of brain function. The ideal approach to calculate the number of synapses per unit volume is to analyze 3D samples reconstructed from serial sections. However, obtaining serial sections by transmission electron microscopy is an extremely time consuming and technically demanding task. Using focused ion beam/scanning electron microscope microscopy, we recently showed that virtually all synapses can be accurately identified as asymmetric or symmetric synapses when they are visualized, reconstructed, and quantified from large 3D tissue samples obtained in an automated manner. Nevertheless, the analysis, segmentation, and quantification of synapses is still a labor intensive procedure. Thus, novel solutions are currently necessary to deal with the large volume of data that is being generated by automated 3D electron microscopy. Accordingly, we have developed ESPINA, a software tool that performs the automated segmentation and counting of synapses in a reconstructed 3D volume of the cerebral cortex, and that greatly facilitates and accelerates these processes.

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Time-resolved reflectance spectroscopy can be used to assess nondestructively the bulk (rather than the superficial) optical properties of highly diffusive media. A fully automated system for time-resolved reflectance spectroscopy was used to evaluate the absorption and the transport scattering spectra of fruits in the red and the near-infrared regions. In particular, data were collected in the range 650-1000 nm from three varieties of apples and from peaches, kiwifruits, and tomatoes. The absorption spectra were usually dominated by the water peak near 970 nm, whereas chlorophyll was detected at 675 nm. For ail species the scattering decreased progressively with increasing wavelength. A best fit to water and chlorophyll absorption line shapes and to Mie theory permitted the estimation of water and chlorophyll content and the average size of scattering centers in the bulls; of intact fruits.

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Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines.

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Aims: A survey to determine the prevalence and numbers of Salmonella in beef cattle presented for slaughter at abattoirs across Australia was conducted between September 2002 and January 2003. Methods and Results: Automated immunomagnetic separation (AIMS) was used for detection and isolation of Salmonella enriched from cattle faeces. Salmonella were enumerated from positive samples using a combination of the Most Probable Number (MPN) technique and AIMS. A total of 310 faecal samples were tested, 155 were from lot-fed cattle and 155 from grass-fed cattle. Salmonella spp. were isolated from 21 (6.8%) of the cattle and the prevalence amongst grass-fed cattle (4.5%) was not significantly different to that found in lot-fed cattle (9%). Counts of Salmonella in positive faeces varied from

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This review will discuss the use of manual grading scales, digital photography, and automated image analysis in the quantification of fundus changes caused by age-related macular disease. Digital imaging permits processing of images for enhancement, comparison, and feature quantification, and these techniques have been investigated for automated drusen analysis. The accuracy of automated analysis systems has been enhanced by the incorporation of interactive elements, such that the user is able to adjust the sensitivity of the system, or manually add and remove pixels. These methods capitalize on both computer and human image feature recognition and the advantage of computer-based methodologies for quantification. The histogram-based adaptive local thresholding system is able to extract useful information from the image without being affected by the presence of other structures. More recent developments involve compensation for fundus background reflectance, which has most recently been combined with the Otsu method of global thresholding. This method is reported to provide results comparable with manual stereo viewing. Developments in this area are likely to encourage wider use of automated techniques. This will make the grading of photographs easier and cheaper for clinicians and researchers. © 2007 Elsevier Inc. All rights reserved.

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The Octopus Automated Perimeter was validated in a comparative study and found to offer many advantages in the assessment of the visual field. The visual evoked potential was investigated in an extensive study using a variety of stimulus parameters to simulate hemianopia and central visual field defects. The scalp topography was recorded topographically and a technique to compute the source derivation of the scalp potential was developed. This enabled clarification of the expected scalp distribution to half field stimulation using different electrode montages. The visual evoked potential following full field stimulation was found to be asymmetrical around the midline with a bias over the left occiput particularly when the foveal polar projections of the occipital cortex were preferentially stimulated. The half field response reflected the distribution asymmetry. Masking of the central 3° resulted in a response which was approximately symmetrical around the midline but there was no evidence of the PNP-complex. A method for visual field quantification was developed based on the neural representation of visual space (Drasdo and Peaston 1982) in an attempt to relate visual field depravation with the resultant visual evoked potentials. There was no form of simple, diffuse summation between the scalp potential and the cortical generators. It was, however, possible to quantify the degree of scalp potential attenuation for M-scaled full field stimuli. The results obtained from patients exhibiting pre-chiasmal lesions suggested that the PNP-complex is not scotomatous in nature but confirmed that it is most likely to be related to specific diseases (Harding and Crews 1982). There was a strong correlation between the percentage information loss of the visual field and the diagnostic value of the visual evoked potential in patients exhibiting chiasmal lesions.

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Background - An evaluation of standard automated perimetry (SAP) and short wavelength automated perimetry (SWAP) for the central 10–2 visual field test procedure in patients with age-related macular degeneration (AMD) is presented in order to determine methods of quantifying the central sensitivity loss in patients at various stages of AMD. Methods - 10–2 SAP and SWAP Humphrey visual fields and stereoscopic fundus photographs were collected in 27 eyes of 27 patients with AMD and 22 eyes of 22 normal subjects. Results - Mean Deviation and Pattern Standard Deviation (PSD) varied significantly with stage of disease in SAP (both p<0.001) and SWAP (both p<0.001), but post hoc analysis revealed overlap of functional values among stages. In SWAP, indices of focal loss were more sensitive to detecting differences in AMD from normal. SWAP defects were greater in depth and area than those in SAP. Central sensitivity (within 1°) changed by -3.9 and -4.9 dB per stage in SAP and SWAP, respectively. Based on defect maps, an AMD Severity Index was derived. Conclusions - Global indices of focal loss were more sensitive to detecting early stage AMD from normal. The SWAP sensitivity decline with advancing stage of AMD was greater than in SAP. A new AMD Severity Index quantifies visual field defects on a continuous scale. Although not all patients are suitable for SWAP examinations, it is of value as a tool in research studies of visual loss in AMD.

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Presentation Purpose:To determine methods of quantifying the sensitivity loss in the central 10o visual field in a cross section of patients at various stages of age-related macular degeneration (AMD). Methods:Standard and short-wavelength automated perimetry (SAP and SWAP) visual fields were collected using program 10-2 of the Humphrey Field Analyzer, in 44 eyes of 27 patients with AMD and 41 eyes of 22 normal subjects. Stereoscopic fundus photographs were graded by two independent observers and the stage of disease determined. Global indices were compared for their ability to delineate the normal visual field from early stages of AMD and to differentiate between stages. Results:Mean Deviation (MD) and Pattern Standard Deviation (PSD) varied significantly with stage of disease in SAP (both p<0.001) and SWAP (both p<0.001), but post-hoc analysis revealed overlap of functional values between stages. Global indices of focal loss, PSD and local spatial variability (LSV) were the most sensitive to detecting differences between normal subjects and early stage AMD patients, in SAP and SWAP, respectively. Overall, defects were confined to the central 5°. SWAP defects were consistently greater in depth and area than those in SAP. The most vulnerable region of the 10° field to sensitivity loss with increasing stage of AMD was the central 1°, in which the sensitivity decline was -4.8dB per stage in SAP and -4.9dB per stage in SWAP. Based on the pattern deviation defect maps, a severity index of AMD visual field loss was derived. Threshold variability was considerably increased in late stage AMD eyes. Conclusions:Global indices of focal loss were more sensitive to the detection of early stage AMD from normal. The sensitivity decline with advancing stage of AMD was greater in SWAP compared to SAP, however the trend was not strong across all stages of disease. The less commonly used index LSV represents relatively statistically unmanipulated summary measure of focal loss. A new severity index is described which is sensitive to visual field change in AMD, measures visual field defects on a continuous scale and may serve as a useful measure of functional change in AMD in longitudinal studies. Keywords: visual fields • age-related macular degeneration • perimetry

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Presentation Purpose:To relate structural change to functional change in age-related macular degeneration (AMD) in a cross-sectional population using fundus imaging and the visual field status. Methods:10 degree standard and SWAP visual fields and other standard functional clinical measures were acquired in 44 eyes of 27 patients at various stages of AMD, as well as fundus photographs. Retro-mode SLO images were captured in a subset of 29 eyes of 19 of the patients. Drusen area, measured by automated drusen segmentation software (Smith et al. 2005) was correlated with visual field data. Visual field defect position was compared to the position of the imaged drusen and deposits using custom software. Results:The effect of AMD stage on drusen area within the 6000µm was significant (One-way ANOVA: F = 17.231, p < 0.001), however the trend was not strong across all stages. There were significant linear relationships between visual field parameters and drusen area. The mean deviation (MD) declined by 3.00dB and 3.92dB for each log % drusen area for standard perimetry and SWAP, respectively. The visual field parameters of focal loss displayed the strongest correlations with drusen area. The number of pattern deviation (PD) defects increased by 9.30 and 9.68 defects per log % drusen area for standard perimetry and SWAP, respectively. Weaker correlations were found between drusen area and visual acuity, contrast sensitivity, colour vision and reading speed. 72.6% of standard PD defects and 65.2% of SWAP PD defects coincided with retinal signs of AMD on fundus photography. 67.5% of standard PD defects and 69.7% of SWAP PD defects coincided with deposits on retro-mode images. Conclusions:Perimetry exhibited a stronger relationship with drusen area than other measures of visual function. The structure-function relationship between visual field parameters and drusen area was linear. Overall the indices of focal loss had a stronger correlation with drusen area in SWAP than in standard perimetry. Visual field defects had a high coincidence proportion with retinal manifestations of AMD.Smith R.T. et al. (2005) Arch Ophthalmol 123:200-206.

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Computed tomography (CT) is a valuable technology to the healthcare enterprise as evidenced by the more than 70 million CT exams performed every year. As a result, CT has become the largest contributor to population doses amongst all medical imaging modalities that utilize man-made ionizing radiation. Acknowledging the fact that ionizing radiation poses a health risk, there exists the need to strike a balance between diagnostic benefit and radiation dose. Thus, to ensure that CT scanners are optimally used in the clinic, an understanding and characterization of image quality and radiation dose are essential.

The state-of-the-art in both image quality characterization and radiation dose estimation in CT are dependent on phantom based measurements reflective of systems and protocols. For image quality characterization, measurements are performed on inserts imbedded in static phantoms and the results are ascribed to clinical CT images. However, the key objective for image quality assessment should be its quantification in clinical images; that is the only characterization of image quality that clinically matters as it is most directly related to the actual quality of clinical images. Moreover, for dose estimation, phantom based dose metrics, such as CT dose index (CTDI) and size specific dose estimates (SSDE), are measured by the scanner and referenced as an indicator for radiation exposure. However, CTDI and SSDE are surrogates for dose, rather than dose per-se.

Currently there are several software packages that track the CTDI and SSDE associated with individual CT examinations. This is primarily the result of two causes. The first is due to bureaucracies and governments pressuring clinics and hospitals to monitor the radiation exposure to individuals in our society. The second is due to the personal concerns of patients who are curious about the health risks associated with the ionizing radiation exposure they receive as a result of their diagnostic procedures.

An idea that resonates with clinical imaging physicists is that patients come to the clinic to acquire quality images so they can receive a proper diagnosis, not to be exposed to ionizing radiation. Thus, while it is important to monitor the dose to patients undergoing CT examinations, it is equally, if not more important to monitor the image quality of the clinical images generated by the CT scanners throughout the hospital.

The purposes of the work presented in this thesis are threefold: (1) to develop and validate a fully automated technique to measure spatial resolution in clinical CT images, (2) to develop and validate a fully automated technique to measure image contrast in clinical CT images, and (3) to develop a fully automated technique to estimate radiation dose (not surrogates for dose) from a variety of clinical CT protocols.

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This report presents a new extraction method of the dinophysistoxins (DTXs), confirmed by quantification using high-performance liquid chromatography coupled to mass spectrometry with an ion trap and electro spray interface (HPLC/ESI/MS2). The method originality consists on the adaptation of DTXs basic extraction procedure (liquid/ liquid) to a solid phase extraction (SPE) via a robotic station: ASPEC XLi The parameters of the automatization procedure were optimized to obtain the best DTXs recovery rate. These improvements were loaded with digestive gland mussel homogenat realized on a silica cartridge SPE, activated in hexane/chloroform (50:50), washed with hexane/chloroform (50:50) and extracted by an elution gradient (chloroform methanol (65:35) and methanol (100%)). This method was validated according to two normative referentials (linearity, detection quantification limits and accuracy…) : - The Guide of the Pharmacy industry: Analytical Validation, report of the commission SFSTP 1992 (French Corporation of the Sciences and Technical Pharmaceutical), - - The Procedure of validation of an alternative method in compare to a reference method. (AFNOR, 1998. NF V 03-110). Comparison with the classical liquid/liquid extraction and the automated method present clear advantages. In an analytical method the extraction is generally considered to be the most labor-intensive and error-prone step. This new procedure allowed us to increase throughput, to improve the reproducibility and to reduce the error risks due to the individual manual treatments.

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A rapid, sensitive and specific method for quantifying propylthiouracil in human plasma using methylthiouracil as the internal standard (IS) is described. The analyte and the IS were extracted from plasma by liquid-liquid extraction using an organic solvent (ethyl acetate). The extracts were analyzed by high performance liquid chromatography coupled with electrospray tandem mass spectrometry (HPLC-MS/MS) in negative mode (ES-). Chromatography was performed using a Phenomenex Gemini C18 5μm analytical column (4.6mm×150mm i.d.) and a mobile phase consisting of methanol/water/acetonitrile (40/40/20, v/v/v)+0.1% of formic acid. For propylthiouracil and I.S., the optimized parameters of the declustering potential, collision energy and collision exit potential were -60 (V), -26 (eV) and -5 (V), respectively. The method had a chromatographic run time of 2.5min and a linear calibration curve over the range 20-5000ng/mL. The limit of quantification was 20ng/mL. The stability tests indicated no significant degradation. This HPLC-MS/MS procedure was used to assess the bioequivalence of two propylthiouracil 100mg tablet formulations in healthy volunteers of both sexes in fasted and fed state. The geometric mean and 90% confidence interval CI of Test/Reference percent ratios were, without and with food, respectively: 109.28% (103.63-115.25%) and 115.60% (109.03-122.58%) for Cmax, 103.31% (100.74-105.96%) and 103.40% (101.03-105.84) for AUClast. This method offers advantages over those previously reported, in terms of both a simple liquid-liquid extraction without clean-up procedures, as well as a faster run time (2.5min). The LOQ of 20ng/mL is well suited for pharmacokinetic studies. The assay performance results indicate that the method is precise and accurate enough for the routine determination of the propylthiouracil in human plasma. The test formulation with and without food was bioequivalent to reference formulation. Food administration increased the Tmax and decreased the bioavailability (Cmax and AUC).

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PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

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OBJECTIVE: This in situ study evaluated the discriminatory power and reliability of methods of dental plaque quantification and the relationship between visual indices (VI) and fluorescence camera (FC) to detect plaque. MATERIAL AND METHODS: Six volunteers used palatal appliances with six bovine enamel blocks presenting different stages of plaque accumulation. The presence of plaque with and without disclosing was assessed using VI. Images were obtained with FC and digital camera in both conditions. The area covered by plaque was assessed. Examinations were done by two independent examiners. Data were analyzed by Kruskal-Wallis and Kappa tests to compare different conditions of samples and to assess the inter-examiner reproducibility. RESULTS: Some methods presented adequate reproducibility. The Turesky index and the assessment of area covered by disclosed plaque in the FC images presented the highest discriminatory powers. CONCLUSION: The Turesky index and images with FC with disclosing present good reliability and discriminatory power in quantifying dental plaque.