Probabilistic Atlas Based Segmentation Using Affine Moment Descriptors and Graph-Cuts

We show a procedure for constructing a probabilistic atlas based on affine moment descriptors. It uses a normalization procedure over the labeled atlas. The proposed linear registration is defined by closed-form expressions involving only geometric moments. This procedure applies both to atlas construction as atlas-based segmentation. We model the likelihood term for each voxel and each label using parametric or nonparametric distributions and the prior term is determined by applying the vote-rule. The probabilistic atlas is built with the variability of our linear registration. We have two segmentation strategy: a) it applies the proposed affine registration to bring the target image into the coordinate frame of the atlas or b) the probabilistic atlas is non-rigidly aligning with the target image, where the probabilistic atlas is previously aligned to the target image with our affine registration. Finally, we adopt a graph cut - Bayesian framework for implementing the atlas-based segmentation.

Raman spectrum of group IV nanowires: influence of temperature

Group IV semiconductor nanowires are characterized by Raman spectroscopy. The results are analyzed in terms of the heating induced by the laser beam on the nanowires. By solving the heat transport equation one can simulate the temperature reached by the NWs under the exposure to a laser beam. The results are illustrated with Si and Si1-xGex nanowires. Both bundles of nanowires and individual nanowires are studied. The main experimental conditions contributing to the nanowire heating are discussed

Structure function and Multifractal spectrum applied to Digital Elevation Model

A Digital Elevation Model (DEM) provides the information basis used for many geographic applications such as topographic and geomorphologic studies, landscape through GIS (Geographic Information Systems) among others. The DEM capacity to represent Earth?s surface depends on the surface roughness and the resolution used. Each DEM pixel depends on the scale used characterized by two variables: resolution and extension of the area studied. DEMs can vary in resolution and accuracy by the production method, although there are statistical characteristics that keep constant or very similar in a wide range of scales. Based on this property, several techniques have been applied to characterize DEM through multiscale analysis directly related to fractal geometry: multifractal spectrum and the structure function. The comparison of the results by both methods is discussed. The study area is represented by a 1024 x 1024 data matrix obtained from a DEM with a resolution of 10 x 10 m each point, which correspond with a region known as ?Monte de El Pardo? a property of Spanish National Heritage (Patrimonio Nacional Español) of 15820 Ha located to a short distance from the center of Madrid. Manzanares River goes through this area from North to South. In the southern area a reservoir is found with a capacity of 43 hm3, with an altitude of 603.3 m till 632 m when it is at the highest capacity. In the middle of the reservoir the minimum altitude of this area is achieved.

A comparison among different spectrum compatible earthquake simulation methods

The need for the simulation of spectrum compatible earthquake time histories has existed since earthquake engineering for complicated structures began. More than the safety of the main structure, the analysis of the equipment (piping, racks, etc.) can only be assessed on the basis of the time history of the floor in which they are contained. This paper presents several methods for calculating simulated spectrum compatible earthquakes as well as a comparison between them. As a result of this comparison, the use of the phase content in real earthquakes as proposed by Ohsaki appears as an effective alternative to the classical methods. With this method, it is possible to establish an approach without the arbitrary modulation commonly used in other methods. Different procedures are described as is the influence of the different parameters which appear in the analysis. Several numerical examples are also presented, and the effectiveness of Ohsaki's method is confirmed.

Graph based study of allergen cross-reactivity of plant lipid transfer proteins (LTPs) using microarray in a multicenter study.

The study of cross-reactivity in allergy is key to both understanding. the allergic response of many patients and providing them with a rational treatment In the present study, protein microarrays and a co-sensitization graph approach were used in conjunction with an allergen microarray immunoassay. This enabled us to include a wide number of proteins and a large number of patients, and to study sensitization profiles among members of the LTP family. Fourteen LTPs from the most frequent plant food-induced allergies in the geographical area studied were printed into a microarray specifically designed for this research. 212 patients with fruit allergy and 117 food-tolerant pollen allergic subjects were recruited from seven regions of Spain with different pollen profiles, and their sera were tested with allergen microarray. This approach has proven itself to be a good tool to study cross-reactivity between members of LTP family, and could become a useful strategy to analyze other families of allergens.

Time series irreversibility: a visibility graph approach

We propose a method to measure real-valued time series irreversibility which combines two different tools: the horizontal visibility algorithm and the Kullback-Leibler divergence. This method maps a time series to a directed network according to a geometric criterion. The degree of irreversibility of the series is then estimated by the Kullback-Leibler divergence (i.e. the distinguishability) between the in and out degree distributions of the associated graph. The method is computationally efficient and does not require any ad hoc symbolization process. We find that the method correctly distinguishes between reversible and irreversible stationary time series, including analytical and numerical studies of its performance for: (i) reversible stochastic processes (uncorrelated and Gaussian linearly correlated), (ii) irreversible stochastic processes (a discrete flashing ratchet in an asymmetric potential), (iii) reversible (conservative) and irreversible (dissipative) chaotic maps, and (iv) dissipative chaotic maps in the presence of noise. Two alternative graph functionals, the degree and the degree-degree distributions, can be used as the Kullback-Leibler divergence argument. The former is simpler and more intuitive and can be used as a benchmark, but in the case of an irreversible process with null net current, the degree-degree distribution has to be considered to identify the irreversible nature of the series

Feigenbaum graphs at the onset of chaos

We analyze the properties of networks obtained from the trajectories of unimodal maps at the transi- tion to chaos via the horizontal visibility (HV) algorithm. We find that the network degrees fluctuate at all scales with amplitude that increases as the size of the network grows, and can be described by a spectrum of graph-theoretical generalized Lyapunov exponents. We further define an entropy growth rate that describes the amount of information created along paths in network space, and find that such en- tropy growth rate coincides with the spectrum of generalized graph-theoretical exponents, constituting a set of Pesin-like identities for the network.

HF spectrum activity prediction model based on HMM for cognitive radio applications

Although most of the research on Cognitive Radio is focused on communication bands above the HF upper limit (30 MHz), Cognitive Radio principles can also be applied to HF communications to make use of the extremely scarce spectrum more efficiently. In this work we consider legacy users as primary users since these users transmit without resorting to any smart procedure, and our stations using the HFDVL (HF Data+Voice Link) architecture as secondary users. Our goal is to enhance an efficient use of the HF band by detecting the presence of uncoordinated primary users and avoiding collisions with them while transmitting in different HF channels using our broad-band HF transceiver. A model of the primary user activity dynamics in the HF band is developed in this work to make short-term predictions of the sojourn time of a primary user in the band and avoid collisions. It is based on Hidden Markov Models (HMM) which are a powerful tool for modelling stochastic random processes and are trained with real measurements of the 14 MHz band. By using the proposed HMM based model, the prediction model achieves an average 10.3% prediction error rate with one minute-long channel knowledge but it can be reduced when this knowledge is extended: with the previous 8 min knowledge, an average 5.8% prediction error rate is achieved. These results suggest that the resulting activity model for the HF band could actually be used to predict primary users activity and included in a future HF cognitive radio based station.

Segmentation of RV in 4D Cardiac MR Volumes using region-merging graph cuts

Non-invasive quantitative assessment of the right ventricular anatomical and functional parameters is a challenging task. We present a semi-automatic approach for right ventricle (RV) segmentation from 4D MR images in two variants, which differ in the amount of user interaction. The method consists of three main phases: First, foreground and background markers are generated from the user input. Next, an over-segmented region image is obtained applying a watershed transform. Finally, these regions are merged using 4D graph-cuts with an intensity based boundary term. For the first variant the user outlines the inside of the RV wall in a few end-diastole slices, for the second two marker pixels serve as starting point for a statistical atlas application. Results were obtained by blind evaluation on 16 testing 4D MR volumes. They prove our method to be robust against markers location and place it favourably in the ranks of existing approaches.

Vanadium-Doped In and Sn Sulphides: Photocatalysts able to use the whole visible light spectrum

Using photocatalysis for energy applications depends, more than for environmental purposes or selective chemical synthesis, on converting as much of the solar spectrum as possible; the best photocatalyst, titania, is far from this. Many efforts are pursued to use better that spectrum in photocatalysis, by doping titania or using other materials (mainly oxides, nitrides and sulphides) to obtain a lower bandgap, even if this means decreasing the chemical potential of the electron-hole pairs. Here we introduce an alternative scheme, using an idea recently proposed for photovoltaics: the intermediate band (IB) materials. It consists in introducing in the gap of a semiconductor an intermediate level which, acting like a stepstone, allows an electron jumping from the valence band to the conduction band in two steps, each one absorbing one sub-bandgap photon. For this the IB must be partially filled, to allow both sub-bandgap transitions to proceed at comparable rates; must be made of delocalized states to minimize nonradiative recombination; and should not communicate electronically with the outer world. For photovoltaic use the optimum efficiency so achievable, over 1.5 times that given by a normal semiconductor, is obtained with an overall bandgap around 2.0 eV (which would be near-optimal also for water phtosplitting). Note that this scheme differs from the doping principle usually considered in photocatalysis, which just tries to decrease the bandgap; its aim is to keep the full bandgap chemical potential but using also lower energy photons. In the past we have proposed several IB materials based on extensively doping known semiconductors with light transition metals, checking first of all with quantum calculations that the desired IB structure results. Subsequently we have synthesized in powder form two of them: the thiospinel In2S3 and the layered compound SnS2 (having bandgaps of 2.0 and 2.2 eV respectively) where the octahedral cation is substituted at a â?10% level with vanadium, and we have verified that this substitution introduces in the absorption spectrum the sub-bandgap features predicted by the calculations. With these materials we have verified, using a simple reaction (formic acid oxidation), that the photocatalytic spectral response is indeed extended to longer wavelengths, being able to use even 700 nm photons, without largely degrading the response for above-bandgap photons (i.e. strong recombination is not induced) [3b, 4]. These materials are thus promising for efficient photoevolution of hydrogen from water; work on this is being pursued, the results of which will be presented.

Interaction between a laser beam and semiconductor nanowires: application to the raman spectrum of Si nanowires

One presents in this work the study of the interaction between a focused laser beam and Si nanowires (NWs). The NWs heating induced by the laser beam is studied by solving the heat transfer equation by finite element methods (fem). This analysis permits to establish the temperature distribution inside the NW when it is excited by the laser beam. The overheating is dependent on the dimensions of the NW, both the diameter and the length. When performing optical characterization of the NWs using focused laser beams, one has to consider the temperature increase introduced by the laser beam. An important issue concerns the fact that the NWs diameter has subwavelength dimensions, and is also smaller than the focused laser beam. The analysis of the thermal behaviour of the NWs under the excitation with the laser beam permits the interpretation of the Raman spectra of Si NWs, where it is demonstrated that temperature induced by the laser beam play a major role in shaping the Raman spectrum of Si NWs

Brain tissue segmentation on Diffusion Weighted Magnetic Resonance data

Introduction Diffusion weighted Imaging (DWI) techniques are able to measure, in vivo and non-invasively, the diffusivity of water molecules inside the human brain. DWI has been applied on cerebral ischemia, brain maturation, epilepsy, multiple sclerosis, etc. [1]. Nowadays, there is a very high availability of these images. DWI allows the identification of brain tissues, so its accurate segmentation is a common initial step for the referred applications. Materials and Methods We present a validation study on automated segmentation of DWI based on the Gaussian mixture and hidden Markov random field models. This methodology is widely solved with iterative conditional modes algorithm, but some studies suggest [2] that graph-cuts (GC) algorithms improve the results when initialization is not close to the final solution. We implemented a segmentation tool integrating ITK with a GC algorithm [3], and a validation software using fuzzy overlap measures [4]. Results Segmentation accuracy of each tool is tested against a gold-standard segmentation obtained from a T1 MPRAGE magnetic resonance image of the same subject, registered to the DWI space. The proposed software shows meaningful improvements by using the GC energy minimization approach on DTI and DSI (Diffusion Spectrum Imaging) data. Conclusions The brain tissues segmentation on DWI is a fundamental step on many applications. Accuracy and robustness improvements are achieved with the proposed software, with high impact on the application’s final result.

Interaction between a laser beam and semiconductor nanowires: application to the raman spectrum of Si nanowires

One presents in this work the study of the interaction between a focused laser beam and Si nanowires (NWs). The NWs heating induced by the laser beam is studied by solving the heat transfer equation by finite element methods (FEM). This analysis permits to establish the temperature distribution inside the NW when it is excited by the laser beam. The overheating is dependent on the dimensions of the NW, both the diameter and the length. When performing optical characterisation of NWs using focused laser beams, one has to consider the temperature increase introduced by the laser beam. An important issue concerns the fact that the NW's diameter has subwavelength dimensions, and is also smaller than the focused laser beam. The analysis of the thermal behaviour of the NWs under the excitation with the laser beam permits the interpretation of the Raman spectrum of Si NWs. It is demonstrated that the temperature increase induced by the laser beam plays a major role in shaping the Raman spectrum of Si NWs.

Evaluation, energy optimization, and spectrum analysis of an artificial noise technique to improve CWSN security

This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number of packets transmitted by the network and the active period of the nodes increase. Security evaluation demonstrates that these techniques are effective against eavesdropper attacks, but also optimization allows for the implementation of these approaches in low-resource networks such as Cognitive Wireless Sensor Networks. In this work, the scenario is formally modeled and the optimization according to the simulation results and the impact analysis over the frequency spectrum are presented.

Processing of ultra-wideband low-frequency signals, for application in Foliage Penetration (FOPEN) Synthetic Aperture Radar (SAR) systems

Foliage Penetration (FOPEN) radar systems were introduced in 1960, and have been constantly improved by several organizations since that time. The use of Synthetic Aperture Radar (SAR) approaches for this application has important advantages, due to the need for high resolution in two dimensions. The design of this type of systems, however, includes some complications that are not present in standard SAR systems. FOPEN SAR systems need to operate with a low central frequency (VHF or UHF bands) in order to be able to penetrate the foliage. High bandwidth is also required to obtain high resolution. Due to the low central frequency, large integration angles are required during SAR image formation, and therefore the Range Migration Algorithm (RMA) is used. This project thesis identifies the three main complications that arise due to these requirements. First, a high fractional bandwidth makes narrowband propagation models no longer valid. Second, the VHF and UHF bands are used by many communications systems. The transmitted signal spectrum needs to be notched to avoid interfering them. Third, those communications systems cause Radio Frequency Interference (RFI) on the received signal. The thesis carries out a thorough analysis of the three problems, their degrading effects and possible solutions to compensate them. The UWB model is applied to the SAR signal, and the degradation induced by it is derived. The result is tested through simulation of both a single pulse stretch processor and the complete RMA image formation. Both methods show that the degradation is negligible, and therefore the UWB propagation effect does not need compensation. A technique is derived to design a notched transmitted signal. Then, its effect on the SAR image formation is evaluated analytically. It is shown that the stretch processor introduces a processing gain that reduces the degrading effects of the notches. The remaining degrading effect after processing gain is assessed through simulation, and an experimental graph of degradation as a function of percentage of nulled frequencies is obtained. The RFI is characterized and its effect on the SAR processor is derived. Once again, a processing gain is found to be introduced by the receiver. As the RFI power can be much higher than that of the desired signal, an algorithm is proposed to remove the RFI from the received signal before RMA processing. This algorithm is a modification of the Chirp Least Squares Algorithm (CLSA) explained in [4], which adapts it to deramped signals. The algorithm is derived analytically and then its performance is evaluated through simulation, showing that it is effective in removing the RFI and reducing the degradation caused by both RFI and notching. Finally, conclusions are drawn as to the importance of each one of the problems in SAR system design.