252 resultados para histogram
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Barrels are discrete cytoarchitectonic neurons cluster located in the layer IV of the somatosensory¦cortex in mice brain. Each barrel is related to a specific whisker located on the mouse snout. The¦whisker-to-barrel pathway is a part of the somatosensory system that is intensively used to explore¦sensory activation induced plasticity in the cerebral cortex.¦Different recording methods exist to explore the cortical response induced by whisker deflection in¦the cortex of anesthetized mice. In this work, we used a method called the Single-Unit Analysis by¦which we recorded the extracellular electric signals of a single barrel neuron using a microelectrode.¦After recording the signal was processed by discriminators to isolate specific neuronal shape (action¦potentials).¦The objective of this thesis was to familiarize with the barrel cortex recording during whisker¦deflection and its theoretical background and to compare two different ways of discriminating and¦sorting cortical signal, the Waveform Window Discriminator (WWD) or the Spike Shape Discriminator (SSD).¦WWD is an electric module allowing the selection of specific electric signal shape. A trigger and a¦window potential level are set manually. During measurements, every time the electric signal passes¦through the two levels a dot is generated on time line. It was the method used in previous¦extracellular recording study in the Département de Biologie Cellulaire et de Morphologie (DBCM) in¦Lausanne.¦SSD is a function provided by the signal analysis software Spike2 (Cambridge Electronic Design). The¦neuronal signal is discriminated by a complex algorithm allowing the creation of specific templates.¦Each of these templates is supposed to correspond to a cell response profile. The templates are saved¦as a number of points (62 in this study) and are set for each new cortical location. During¦measurements, every time the cortical recorded signal corresponds to a defined number of templates¦points (60% in this study) a dot is generated on time line. The advantage of the SSD is that multiple¦templates can be used during a single stimulation, allowing a simultaneous recording of multiple¦signals.¦It exists different ways to represent data after discrimination and sorting. The most commonly used¦in the Single-Unit Analysis of the barrel cortex are the representation of the time between stimulation¦and the first cell response (the latency), the representation of the Response Magnitude (RM) after¦whisker deflection corrected for spontaneous activity and the representation of the time distribution¦of neuronal spikes on time axis after whisker stimulation (Peri-Stimulus Time Histogram, PSTH).¦The results show that the RMs and the latencies in layer IV were significantly different between the¦WWD and the SSD discriminated signal. The temporal distribution of the latencies shows that the¦different values were included between 6 and 60ms with no peak value for SSD while the WWD¦data were all gathered around a peak of 11ms (corresponding to previous studies). The scattered¦distribution of the latencies recorded with the SSD did not correspond to a cell response.¦The SSD appears to be a powerful tool for signal sorting but we do not succeed to use it for the¦Single-Unit Analysis extracellular recordings. Further recordings with different SSD templates settings¦and larger sample size may help to show the utility of this tool in Single-Unit Analysis studies.
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Micas are commonly used in Ar-40/Ar-39 thermochronological studies of variably deformed rocks yet the physical basis by which deformation may affect radiogenic argon retention in mica is poorly constrained. This study examines the relationship between deformation and deformation-induced microstructures on radiogenic argon retention in muscovite, A combination of furnace step-heating and high-spatial resolution in situ UV-laser ablation Ar-40/Ar-39 analyses are reported for deformed muscovites sampled from a granitic pegmatite vein within the Siviez-Mischabel Nappe, western Swiss Alps (Penninic domain, Brianconnais unit). The pegmatite forms part of the Variscan (similar to 350 Ma) Alpine basement and exhibits a prominent Alpine S-C fabric including numerous mica `fish' that developed under greenschist facies metamorphic conditions, during the dominant Tertiary Alpine tectonic phase of nappe emplacement. Furnace step-heating of milligram quantities of separated muscovite grains yields an Ar-40/Ar-39 age spectrum with two distinct staircase segments but without any statistical plateau, consistent with a previous study from the same area. A single (3 X 5 mm) muscovite porphyroclast (fish) was investigated by in situ UV-laser ablation. A histogram plot of 170 individual Ar-40/Ar-39 UV-laser ablation ages exhibit a range from 115 to 387 Ma with modes at approximately 340 and 260 Ma. A variogram statistical treatment of the (40)Ad/Ar-39 results reveals ages correlated with two directions; a highly correlated direction at 310 degrees and a lesser correlation at 0 degrees relative to the sense of shearing. Using the highly correlated direction a statistically generated (Kriging method) age contour map of the Ar-40/Ar-39 data reveals a series of elongated contours subparallel to the C-surfaces which where formed during Tertiary nappe emplacement. Similar data distributions and slightly younger apparent ages are recognized in a smaller mica fish. The observed intragrain age variations are interpreted to reflect the partial loss of radiogenic argon during Alpine (similar to 35 Ma) greenschist facies metamorphism. One-dirnensional diffusion modelling results are consistent with the idea that the zones of youngest apparent age represent incipient shear band development within the mica porphyroclasts, thus providing a network of fast diffusion pathways. During Alpine greenschist facies metamorphism the incipient shear bands enhanced the intragrain loss of radiogenic argon. The structurally controlled intragrain age variations observed in this investigation imply that deformation has a direct control on the effective length scale for argon diffusion, which is consistent with the heterogeneous nature of deformation. (C) 2001 Elsevier Science B.V. All rights reserved.
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Statistical computing when input/output is driven by a Graphical User Interface is considered. A proposal is made for automatic control ofcomputational flow to ensure that only strictly required computationsare actually carried on. The computational flow is modeled by a directed graph for implementation in any object-oriented programming language with symbolic manipulation capabilities. A complete implementation example is presented to compute and display frequency based piecewise linear density estimators such as histograms or frequency polygons.
Characterization of intonation in Karṇāṭaka music by parametrizing context-based Svara Distributions
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Intonation is a fundamental music concept that has a special relevance in Indian art music. It is characteristic of the rāga and intrinsic to the musical expression of the performer. Describing intonation is of importance to several information retrieval tasks like the development of rāga and artist similarity measures. In our previous work, we proposed a compact representation of intonation based on the parametrization of the pitch histogram of a performance and demonstrated the usefulness of this representation through an explorative rāga recognition task in which we classified 42 vocal performances belonging to 3 rāgas using parameters of a single svara. In this paper, we extend this representation to employ context-based svara distributions, which are obtained with a different approach to find the pitches belonging to each svara. We quantitatively compare this method to our previous one, discuss the advantages, and the necessary melodic analysis to be carried out in future.
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AIM: MRI and PET with 18F-fluoro-ethyl-tyrosine (FET) have been increasingly used to evaluate patients with gliomas. Our purpose was to assess the additive value of MR spectroscopy (MRS), diffusion imaging and dynamic FET-PET for glioma grading. PATIENTS, METHODS: 38 patients (42 ± 15 aged, F/M: 0.46) with untreated histologically proven brain gliomas were included. All underwent conventional MRI, MRS, diffusion sequences, and FET-PET within 3±4 weeks. Performances of tumour FET time-activity-curve, early-to-middle SUVmax ratio, choline / creatine ratio and ADC histogram distribution pattern for gliomas grading were assessed, as compared to histology. Combination of these parameters and respective odds were also evaluated. RESULTS: Tumour time-activity-curve reached the best accuracy (67%) when taken alone to distinguish between low and high-grade gliomas, followed by ADC histogram analysis (65%). Combination of time-activity-curve and ADC histogram analysis improved the sensitivity from 67% to 86% and the specificity from 63-67% to 100% (p < 0.008). On multivariate logistic regression analysis, negative slope of the tumour FET time-activity-curve however remains the best predictor of high-grade glioma (odds 7.6, SE 6.8, p = 0.022). CONCLUSION: Combination of dynamic FET-PET and diffusion MRI reached good performance for gliomas grading. The use of FET-PET/MR may be highly relevant in the initial assessment of primary brain tumours.
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In Neo-Darwinism, variation and natural selection are the two evolutionary mechanisms which propel biological evolution. Our previous article presented a histogram model [1] consisting in populations of individuals whose number changed under the influence of variation and/or fitness, the total population remaining constant. Individuals are classified into bins, and the content of each bin is calculated generation after generation by an Excel spreadsheet. Here, we apply the histogram model to a stable population with fitness F(1)=1.00 in which one or two fitter mutants emerge. In a first scenario, a single mutant emerged in the population whose fitness was greater than 1.00. The simulations ended when the original population was reduced to a single individual. The histogram model was validated by excellent agreement between its predictions and those of a classical continuous function (Eqn. 1) which predicts the number of generations needed for a favorable mutation to spread throughout a population. But in contrast to Eqn. 1, our histogram model is adaptable to more complex scenarios, as demonstrated here. In the second and third scenarios, the original population was present at time zero together with two mutants which differed from the original population by two higher and distinct fitness values. In the fourth scenario, the large original population was present at time zero together with one fitter mutant. After a number of generations, when the mutant offspring had multiplied, a second mutant was introduced whose fitness was even greater. The histogram model also allows Shannon entropy (SE) to be monitored continuously as the information content of the total population decreases or increases. The results of these simulations illustrate, in a graphically didactic manner, the influence of natural selection, operating through relative fitness, in the emergence and dominance of a fitter mutant.
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AIM: MRI and PET with 18F-fluoro-ethyl-tyrosine (FET) have been increasingly used to evaluate patients with gliomas. Our purpose was to assess the additive value of MR spectroscopy (MRS), diffusion imaging and dynamic FET-PET for glioma grading. PATIENTS, METHODS: 38 patients (42 ± 15 aged, F/M: 0.46) with untreated histologically proven brain gliomas were included. All underwent conventional MRI, MRS, diffusion sequences, and FET-PET within 3±4 weeks. Performances of tumour FET time-activity-curve, early-to-middle SUVmax ratio, choline / creatine ratio and ADC histogram distribution pattern for gliomas grading were assessed, as compared to histology. Combination of these parameters and respective odds were also evaluated. RESULTS: Tumour time-activity-curve reached the best accuracy (67%) when taken alone to distinguish between low and high-grade gliomas, followed by ADC histogram analysis (65%). Combination of time-activity-curve and ADC histogram analysis improved the sensitivity from 67% to 86% and the specificity from 63-67% to 100% (p < 0.008). On multivariate logistic regression analysis, negative slope of the tumour FET time-activity-curve however remains the best predictor of high-grade glioma (odds 7.6, SE 6.8, p = 0.022). CONCLUSION: Combination of dynamic FET-PET and diffusion MRI reached good performance for gliomas grading. The use of FET-PET/MR may be highly relevant in the initial assessment of primary brain tumours.
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Objective: To implement a carotid sparing protocol using helical Tomotherapy(HT) in T1N0 squamous-cell laryngeal carcinoma.Materials/Methods: Between July and August 2010, 7 men with stage T1N0 laryngeal carcinoma were included in this study. Age ranged from 47-74 years. Staging included endoscopic examination, CT-scan and MRI when indicated.Planned irradiation dose was 70 Gy in 35 fractions over 7 weeks. A simple treatment planning algorithm for carotidsparing was used: maximum point dose to the carotids 35 Gy, to the spinal cord 30 Gy, and 100% PTV volume to becovered with 95% of the prescribed dose. Carotid volume of interest extended to 1 cm above and below of the PTV.Doses to the carotid arteries, critical organs, and planned target volume (PTV) with our standard laryngealirradiation protocol was compared. Daily megavoltage scans were obtained before each fraction. When necessary, thePlanned Adaptive? software (TomoTherapy Inc., Madison, WI) was used to evaluate the need for a re-planning,which has never been indicated. Dose data were extracted using the VelocityAI software (Atlanta, GA), and datanormalization and dosevolume histogram (DVH) interpolation were realized using the Igor Pro software (Portland,OR).Results: A significant (p < 0.05) carotid dose sparing compared to our standard protocol with an average maximum point dose of 38.3 Gy (standard devaition [SD] 4.05 Gy), average mean dose of 18.59 Gy (SD 0.83 Gy) was achieved.In all patients, 95% of the carotid volume received less than 28.4 Gy (SD 0.98 Gy). The average maximum point doseto the spinal cord was 25.8 Gy (SD 3.24 Gy). PTV was fully covered with more than 95% of the prescribed dose forall patients with an average maximum point dose of 74.1 Gy and the absolute maximum dose in a single patient of75.2 Gy. To date, the clinical outcomes have been excellent. Three patients (42%) developed stage 1 mucositis that was conservatively managed, and all the patients presented a mild to moderate dysphonia. All adverse effectsresolved spontaneously in the month following the end of treatment. Early local control rate is 100% considering a 4-5months post treatment follow-up.Conclusions: HT allows a clinically significant decrease of carotid irradiation dose compared tostandard irradiation protocols with an acceptable spinal cord dose tradeoff. Moreover, this technique allows the PTV to be homogenously covered with a curative irradiation dose. Daily control imaging brings added security marginsespecially when working with high dose gradients. Further investigations and follow-up are underway to better evaluatethe late clinical outcomes especially the local control rate, late laryngeal and vascular toxicity, and expected potentialimpact on cerebrovascular events.
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BACKGROUND: Whole pelvis intensity modulated radiotherapy (IMRT) is increasingly being used to treat cervical cancer aiming to reduce side effects. Encouraged by this, some groups have proposed the use of simultaneous integrated boost (SIB) to target the tumor, either to get a higher tumoricidal effect or to replace brachytherapy. Nevertheless, physiological organ movement and rapid tumor regression throughout treatment might substantially reduce any benefit of this approach. PURPOSE: To evaluate the clinical target volume - simultaneous integrated boost (CTV-SIB) regression and motion during chemo-radiotherapy (CRT) for cervical cancer, and to monitor treatment progress dosimetrically and volumetrically to ensure treatment goals are met. METHODS AND MATERIALS: Ten patients treated with standard doses of CRT and brachytherapy were retrospectively re-planned using a helical Tomotherapy - SIB technique for the hypothetical scenario of this feasibility study. Target and organs at risk (OAR) were contoured on deformable fused planning-computed tomography and megavoltage computed tomography images. The CTV-SIB volume regression was determined. The center of mass (CM) was used to evaluate the degree of motion. The Dice's similarity coefficient (DSC) was used to assess the spatial overlap of CTV-SIBs between scans. A cumulative dose-volume histogram modeled estimated delivered doses. RESULTS: The CTV-SIB relative reduction was between 31 and 70%. The mean maximum CM change was 12.5, 9, and 3 mm in the superior-inferior, antero-posterior, and right-left dimensions, respectively. The CTV-SIB-DSC approached 1 in the first week of treatment, indicating almost perfect overlap. CTV-SIB-DSC regressed linearly during therapy, and by the end of treatment was 0.5, indicating 50% discordance. Two patients received less than 95% of the prescribed dose. Much higher doses to the OAR were observed. A multiple regression analysis showed a significant interaction between CTV-SIB reduction and OAR dose increase. CONCLUSIONS: The CTV-SIB had important regression and motion during CRT, receiving lower therapeutic doses than expected. The OAR had unpredictable shifts and received higher doses. The use of SIB without frequent adaptation of the treatment plan exposes cervical cancer patients to an unpredictable risk of under-dosing the target and/or overdosing adjacent critical structures. In that scenario, brachytherapy continues to be the gold standard approach.
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In Neo-Darwinism, variation and natural selection are the two evolutionary mechanisms which propel biological evolution. Our previous reports presented a histogram model to simulate the evolution of populations of individuals classified into bins according to an unspecified, quantifiable phenotypic character, and whose number in each bin changed generation after generation under the influence of fitness, while the total population was maintained constant. The histogram model also allowed Shannon entropy (SE) to be monitored continuously as the information content of the total population decreased or increased. Here, a simple Perl (Practical Extraction and Reporting Language) application was developed to carry out these computations, with the critical feature of an added random factor in the percent of individuals whose offspring moved to a vicinal bin. The results of the simulations demonstrate that the random factor mimicking variation increased considerably the range of values covered by Shannon entropy, especially when the percentage of changed offspring was high. This increase in information content is interpreted as facilitated adaptability of the population.
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The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.
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In this paper, we describe several techniques for detecting tonic pitch value in Indian classical music. In Indian music, the raga is the basic melodic framework and it is built on the tonic. Tonic detection is therefore fundamental for any melodic analysis in Indian classical music. This workexplores detection of tonic by processing the pitch histograms of Indian classic music. Processing of pitch histograms using group delay functions and its ability to amplify certain traits of Indian music in the pitch histogram, is discussed. Three different strategies to detect tonic, namely, the concert method, the template matching and segmented histogram method are proposed. The concert method exploits the fact that the tonic is constant over a piece/concert.templatematchingmethod and segmented histogrammethodsuse the properties: (i) the tonic is always present in the background, (ii) some notes are less inflected and dominant, to detect the tonic of individual pieces. All the three methods yield good results for Carnatic music (90−100% accuracy), while for Hindustanimusic, the templatemethod works best, provided the v¯adi samv¯adi notes for a given piece are known (85%).
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BACKGROUND: The purpose of this study was to explore the potential use of image analysis on tissue sections preparation as a predictive marker of early malignant changes during squamous cell (SC) carcinogenesis in the esophagus. Results of DNA ploidy quantification on formalin-fixed, paraffin-embedded tissue using two different techniques were compared: imprint-cytospin and 6 microm thick tissue sections preparation. METHODS: This retrospective study included 26 surgical specimens of squamous cell carcinoma (SCC) from patients who underwent surgery alone at the Department of Surgery in CHUV Hospital in Lausanne between January 1993 and December 2000. We analyzed 53 samples of healthy tissue, 43 tumors and 7 lymph node metastases. RESULTS: Diploid DNA histogram patterns were observed in all histologically healthy tissues, either distant or proximal to the lesion. Aneuploidy was observed in 34 (79%) of 43 carcinomas, namely 24 (75%) of 32 early squamous cell carcinomas and 10 (91%) of 11 advanced carcinomas. DNA content was similar in the different tumor stages, whether patients presented with single or multiple synchronous tumors. All lymph node metastases had similar DNA content as their primary tumor. CONCLUSIONS: Early malignant changes in the esophagus are associated with alteration in DNA content, and aneuploidy tends to correlate with progression of invasive SCC. A very good correlation between imprint-cytospin and tissue section analysis was observed. Although each method used here showed advantages and disadvantages; tissue sections preparation provided useful information on aberrant cell-cycle regulation and helped select the optimal treatment for the individual patient along with consideration of other clinical parameters.
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This article reports on a lossless data hiding scheme for digital images where the data hiding capacity is either determined by minimum acceptable subjective quality or by the demanded capacity. In the proposed method data is hidden within the image prediction errors, where the most well-known prediction algorithms such as the median edge detector (MED), gradient adjacent prediction (GAP) and Jiang prediction are tested for this purpose. In this method, first the histogram of the prediction errors of images are computed and then based on the required capacity or desired image quality, the prediction error values of frequencies larger than this capacity are shifted. The empty space created by such a shift is used for embedding the data. Experimental results show distinct superiority of the image prediction error histogram over the conventional image histogram itself, due to much narrower spectrum of the former over the latter. We have also devised an adaptive method for hiding data, where subjective quality is traded for data hiding capacity. Here the positive and negative error values are chosen such that the sum of their frequencies on the histogram is just above the given capacity or above a certain quality.
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In this paper we introduce a highly efficient reversible data hiding system. It is based on dividing the image into tiles and shifting the histograms of each image tile between its minimum and maximum frequency. Data are then inserted at the pixel level with the largest frequency to maximize data hiding capacity. It exploits the special properties of medical images, where the histogram of their nonoverlapping image tiles mostly peak around some gray values and the rest of the spectrum is mainlyempty. The zeros (or minima) and peaks (maxima) of the histograms of the image tiles are then relocated to embed the data. The grey values of some pixels are therefore modified.High capacity, high fidelity, reversibility and multiple data insertions are the key requirements of data hiding in medical images. We show how histograms of image tiles of medical images can be exploited to achieve these requirements. Compared with data hiding method applied to the whole image, our scheme can result in 30%-200% capacity improvement and still with better image quality, depending on the medical image content. Additional advantages of the proposed method include hiding data in the regions of non-interest and better exploitation of spatial masking.