Content Based Image Retrieval Using Low Level Features of Automatically Extracted Regions of Interest

This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.

A Sub-block Based Image Retrieval Using Modified Integrated Region Matching.

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). A modified Integrated Region Matching (IRM) algorithm is used for finding the minimum distance between the sub-blocks of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

Revisión sistemática : uso de imágenes por difusión en RMN, para predecir sobrevida en pacientes adultos con diagnostico de glioblastoma multiforme

El Glioblastoma multiforme (GBM), es el tumor cerebral más frecuente, con pronóstico grave y baja sensibilidad al tratamiento inicial. El propósito de este estudio fue evaluar si la Difusión en RM (IDRM), es un biomarcador temprano de respuesta tumoral, útil para tomar decisiones tempranas de tratamiento y para obtener información pronostica. Metodología La búsqueda se realizo en las bases de datos EMBASE, CENTRAL, MEDLINE; las bibliografías también fueron revisadas. Los artículos seleccionados fueron estudios observacionales (casos y controles, cohortes, corte transversal), no se encontró ningún ensayo clínico; todos los participante tenían diagnostico histopatológico de GBM, sometidos a resección quirúrgica y/o radio-quimioterapia y seguimiento de respuesta al tratamiento con IDRM por al menos 6 meses. Los datos extraídos de forma independiente fueron tipo de estudio, participantes, intervenciones, seguimiento, desenlaces (sobrevida, progresión/estabilización de la enfermedad, muerte) Resultados Quince estudios cumplieron los criterios de inclusión. Entre las técnicas empleadas de IDRM para evaluar respuesta radiológica al tratamiento, fueron histogramas del coeficiente aparente de difusion ADC (compararon valores inferiores a la media y el percentil 10 de ADC, con los valores superiores); encontrando en términos generales que un ADC bajo es un fuerte predictor de sobrevida y/o progresión del tumor. (Esto fue significativo en 5 estudios); mapas funcionales de difusion (FDM) (midieron el porcentaje de cambio de ADC basal vs pos tratamiento) que mostro ser un fuerte predictor de sobrevida en pacientes con progresión tumoral. DISCUSION Desafortunadamente la calidad de los estudios fue intermedia-baja lo que hace que la aplicabilidad de los estudios sea limitada.

Cell and nuclear degradation in sweetpotato [Ipomoea batatas (L.) Lam.] root meristems following exposure to salinity

Sodium chloride-induced cell and nuclear degradation in the root meristems of sweetpotato [Ipomoea batatas (L.) Lam.] were determined using fluorescent microscopy and flow cytometry analysis. Two sweetpotato cultivars were grown in liquid Murashige and Skoog medium and subjected to 0 mM and 500 mM NaCl, with or without 15 mM CaCl2, for periods up to 24 h. Changes to the nuclei of root meristematic cells showed a similar pattern of damage to the nuclei using both fluorescent microscopy and flow cytometry analysis. Damage occurring after only a few hours was followed by nuclear degradation at 24 h. Flow cytometry histograms showed a reduction in G1 and G2 nuclei and an increase in degraded nuclei in NaCl-stressed roots. Salinity-induced nuclear degradation was alleviated by the addition of CaCl2.

Integrating features for man-made target tracking from FLIR image sequence using particle filter

A new man-made target tracking algorithm integrating features from (Forward Looking InfraRed) image sequence is presented based on particle filter. Firstly, a multiscale fractal feature is used to enhance targets in FLIR images. Secondly, the gray space feature is defined by Bhattacharyya distance between intensity histograms of the reference target and a sample target from MFF (Multi-scale Fractal Feature) image. Thirdly, the motion feature is obtained by differencing between two MFF images. Fourthly, a fusion coefficient can be automatically obtained by online feature selection method for features integrating based on fuzzy logic. Finally, a particle filtering framework is developed to fulfill the target tracking. Experimental results have shown that the proposed algorithm can accurately track weak or small man-made target in FLIR images with complicated background. The algorithm is effective, robust and satisfied to real time tracking.

Transport in the low-latitude tropopause zone diagnosed using particle trajectories

Recent literature has described a “transition zone” between the average top of deep convection in the Tropics and the stratosphere. Here transport across this zone is investigated using an offline trajectory model. Particles were advected by the resolved winds from the European Centre for Medium-Range Weather Forecasts reanalyses. For each boreal winter clusters of particles were released in the upper troposphere over the four main regions of tropical deep convection (Indonesia, central Pacific, South America, and Africa). Most particles remain in the troposphere, descending on average for every cluster. The horizontal components of 5-day trajectories are strongly influenced by the El Niño–Southern Oscillation (ENSO), but the Lagrangian average descent does not have a clear ENSO signature. Tropopause crossing locations are first identified by recording events when trajectories from the same release regions cross the World Meteorological Organization lapse rate tropopause. Most crossing events occur 5–15 days after release, and 30-day trajectories are sufficiently long to estimate crossing number densities. In a further two experiments slight excursions across the lapse rate tropopause are differentiated from the drift deeper into the stratosphere by defining the “tropopause zone” as a layer bounded by the average potential temperature of the lapse rate tropopause and the profile temperature minimum. Transport upward across this zone is studied using forward trajectories released from the lower bound and back trajectories arriving at the upper bound. Histograms of particle potential temperature (θ) show marked differences between the transition zone, where there is a slow spread in θ values about a peak that shifts slowly upward, and the troposphere below 350 K. There forward trajectories experience slow radiative cooling interspersed with bursts of convective heating resulting in a well-mixed distribution. In contrast θ histograms for back trajectories arriving in the stratosphere have two distinct peaks just above 300 and 350 K, indicating the sharp change from rapid convective heating in the well-mixed troposphere to slow ascent in the transition zone. Although trajectories slowly cross the tropopause zone throughout the Tropics, all three experiments show that most trajectories reaching the stratosphere from the lower troposphere within 30 days do so over the west Pacific warm pool. This preferred location moves about 30°–50° farther east in an El Niño year (1982/83) and about 30° farther west in a La Niña year (1988/89). These results could have important implications for upper-troposphere–lower-stratosphere pollution and chemistry studies.

Characterising the variability and extremes of the stratospheric polar vortices using 2D moment analysis

The mean state, variability and extreme variability of the stratospheric polar vortices, with an emphasis on the Northern Hemisphere vortex, are examined using 2-dimensional moment analysis and Extreme Value Theory (EVT). The use of moments as an analysis to ol gives rise to information about the vortex area, centroid latitude, aspect ratio and kurtosis. The application of EVT to these moment derived quantaties allows the extreme variability of the vortex to be assessed. The data used for this study is ECMWF ERA-40 potential vorticity fields on interpolated isentropic surfaces that range from 450K-1450K. Analyses show that the most extreme vortex variability occurs most commonly in late January and early February, consistent with when most planetary wave driving from the troposphere is observed. Composites around sudden stratospheric warming (SSW) events reveal that the moment diagnostics evolve in statistically different ways between vortex splitting events and vortex displacement events, in contrast to the traditional diagnostics. Histograms of the vortex diagnostics on the 850K (∼10hPa) surface over the 1958-2001 period are fitted with parametric distributions, and show that SSW events comprise the majority of data in the tails of the distributions. The distribution of each diagnostic is computed on various surfaces throughout the depth of the stratosphere, and shows that in general the vortex becomes more circular with higher filamentation at the upper levels. The Northern Hemisphere (NH) and Southern Hemisphere (SH) vortices are also compared through the analysis of their respective vortex diagnostics, and confirm that the SH vortex is less variable and lacks extreme events compared to the NH vortex. Finally extreme value theory is used to statistically mo del the vortex diagnostics and make inferences about the underlying dynamics of the polar vortices.

Ensemble prediction for nowcasting with a convection-permitting model—I: description of the system and the impact of radar-derived surface precipitation rates

A key strategy to improve the skill of quantitative predictions of precipitation, as well as hazardous weather such as severe thunderstorms and flash floods is to exploit the use of observations of convective activity (e.g. from radar). In this paper, a convection-permitting ensemble prediction system (EPS) aimed at addressing the problems of forecasting localized weather events with relatively short predictability time scale and based on a 1.5 km grid-length version of the Met Office Unified Model is presented. Particular attention is given to the impact of using predicted observations of radar-derived precipitation intensity in the ensemble transform Kalman filter (ETKF) used within the EPS. Our initial results based on the use of a 24-member ensemble of forecasts for two summer case studies show that the convective-scale EPS produces fairly reliable forecasts of temperature, horizontal winds and relative humidity at 1 h lead time, as evident from the inspection of rank histograms. On the other hand, the rank histograms seem also to show that the EPS generates too much spread for forecasts of (i) surface pressure and (ii) surface precipitation intensity. These may indicate that for (i) the value of surface pressure observation error standard deviation used to generate surface pressure rank histograms is too large and for (ii) may be the result of non-Gaussian precipitation observation errors. However, further investigations are needed to better understand these findings. Finally, the inclusion of predicted observations of precipitation from radar in the 24-member EPS considered in this paper does not seem to improve the 1-h lead time forecast skill.

Parallel pipelined array architectures for real-time histogram computation in consumer devices

The real-time parallel computation of histograms using an array of pipelined cells is proposed and prototyped in this paper with application to consumer imaging products. The array operates in two modes: histogram computation and histogram reading. The proposed parallel computation method does not use any memory blocks. The resulting histogram bins can be stored into an external memory block in a pipelined fashion for subsequent reading or streaming of the results. The array of cells can be tuned to accommodate the required data path width in a VLSI image processing engine as present in many imaging consumer devices. Synthesis of the architectures presented in this paper in FPGA are shown to compute the real-time histogram of images streamed at over 36 megapixels at 30 frames/s by processing in parallel 1, 2 or 4 pixels per clock cycle.

On reliability analysis of multi-categorical forecasts

Reliability analysis of probabilistic forecasts, in particular through the rank histogram or Talagrand diagram, is revisited. Two shortcomings are pointed out: Firstly, a uniform rank histogram is but a necessary condition for reliability. Secondly, if the forecast is assumed to be reliable, an indication is needed how far a histogram is expected to deviate from uniformity merely due to randomness. Concerning the first shortcoming, it is suggested that forecasts be grouped or stratified along suitable criteria, and that reliability is analyzed individually for each forecast stratum. A reliable forecast should have uniform histograms for all individual forecast strata, not only for all forecasts as a whole. As to the second shortcoming, instead of the observed frequencies, the probability of the observed frequency is plotted, providing and indication of the likelihood of the result under the hypothesis that the forecast is reliable. Furthermore, a Goodness-Of-Fit statistic is discussed which is essentially the reliability term of the Ignorance score. The discussed tools are applied to medium range forecasts for 2 m-temperature anomalies at several locations and lead times. The forecasts are stratified along the expected ranked probability score. Those forecasts which feature a high expected score turn out to be particularly unreliable.

The concept of exchangeability in ensemble forecasting

A set of random variables is exchangeable if its joint distribution function is invariant under permutation of the arguments. The concept of exchangeability is discussed, with a view towards potential application in evaluating ensemble forecasts. It is argued that the paradigm of ensembles being an independent draw from an underlying distribution function is probably too narrow; allowing ensemble members to be merely exchangeable might be a more versatile model. The question is discussed whether established methods of ensemble evaluation need alteration under this model, with reliability being given particular attention. It turns out that the standard methodology of rank histograms can still be applied. As a first application of the exchangeability concept, it is shown that the method of minimum spanning trees to evaluate the reliability of high dimensional ensembles is mathematically sound.

Evaluating raw ensembles with the continuous ranked probability score

The continuous ranked probability score (CRPS) is a frequently used scoring rule. In contrast with many other scoring rules, the CRPS evaluates cumulative distribution functions. An ensemble of forecasts can easily be converted into a piecewise constant cumulative distribution function with steps at the ensemble members. This renders the CRPS a convenient scoring rule for the evaluation of ‘raw’ ensembles, obviating the need for sophisticated ensemble model output statistics or dressing methods prior to evaluation. In this article, a relation between the CRPS score and the quantile score is established. The evaluation of ‘raw’ ensembles using the CRPS is discussed in this light. It is shown that latent in this evaluation is an interpretation of the ensemble as quantiles but with non-uniform levels. This needs to be taken into account if the ensemble is evaluated further, for example with rank histograms.

Parallel pipelined histogram architecture via c-slow retiming

A parallel pipelined array of cells suitable for realtime computation of histograms is proposed. The cell architecture builds on previous work to now allow operating on a stream of data at 1 pixel per clock cycle. This new cell is more suitable for interfacing to camera sensors or to microprocessors of 8-bit data buses which are common in consumer digital cameras. Arrays using the new proposed cells are obtained via C-slow retiming techniques and can be clocked at a 65% faster frequency than previous arrays. This achieves over 80% of the performance of two-pixel per clock cycle parallel pipelined arrays.

Assessment of inter-examiner agreement and variability in the manual classification of auditory brainstem response

Abstract Background: The analysis of the Auditory Brainstem Response (ABR) is of fundamental importance to the investigation of the auditory system behaviour, though its interpretation has a subjective nature because of the manual process employed in its study and the clinical experience required for its analysis. When analysing the ABR, clinicians are often interested in the identification of ABR signal components referred to as Jewett waves. In particular, the detection and study of the time when these waves occur (i.e., the wave latency) is a practical tool for the diagnosis of disorders affecting the auditory system. Significant differences in inter-examiner results may lead to completely distinct clinical interpretations of the state of the auditory system. In this context, the aim of this research was to evaluate the inter-examiner agreement and variability in the manual classification of ABR. Methods: A total of 160 ABR data samples were collected, for four different stimulus intensity (80dBHL, 60dBHL, 40dBHL and 20dBHL), from 10 normal-hearing subjects (5 men and 5 women, from 20 to 52 years). Four examiners with expertise in the manual classification of ABR components participated in the study. The Bland-Altman statistical method was employed for the assessment of inter-examiner agreement and variability. The mean, standard deviation and error for the bias, which is the difference between examiners’ annotations, were estimated for each pair of examiners. Scatter plots and histograms were employed for data visualization and analysis. Results: In most comparisons the differences between examiner’s annotations were below 0.1 ms, which is clinically acceptable. In four cases, it was found a large error and standard deviation (>0.1 ms) that indicate the presence of outliers and thus, discrepancies between examiners. Conclusions: Our results quantify the inter-examiner agreement and variability of the manual analysis of ABR data, and they also allows for the determination of different patterns of manual ABR analysis.

C-slow retimed parallel histogram architectures for consumer imaging devices

A parallel pipelined array of cells suitable for real-time computation of histograms is proposed. The cell architecture builds on previous work obtained via C-slow retiming techniques and can be clocked at 65 percent faster frequency than previous arrays. The new arrays can be exploited for higher throughput particularly when dual data rate sampling techniques are used to operate on single streams of data from image sensors. In this way, the new cell operates on a p-bit data bus which is more convenient for interfacing to camera sensors or to microprocessors in consumer digital cameras.