Intensity Segmentation of the Human Brain with Tissue dependent Homogenization

High-precision segmentation of the human cerebral cortex based on T1-weighted MRI is still a challenging task. When opting to use an intensity based approach, careful data processing is mandatory to overcome inaccuracies. They are caused by noise, partial volume effects and systematic signal intensity variations imposed by limited homogeneity of the acquisition hardware. We propose an intensity segmentation which is free from any shape prior. It uses for the first time alternatively grey (GM) or white matter (WM) based homogenization. This new tissue dependency was introduced as the analysis of 60 high resolution MRI datasets revealed appreciable differences in the axial bias field corrections, depending if they are based on GM or WM. Homogenization starts with axial bias correction, a spatially irregular distortion correction follows and finally a noise reduction is applied. The construction of the axial bias correction is based on partitions of a depth histogram. The irregular bias is modelled by Moody Darken radial basis functions. Noise is eliminated by nonlinear edge preserving and homogenizing filters. A critical point is the estimation of the training set for the irregular bias correction in the GM approach. Because of intensity edges between CSF (cerebro spinal fluid surrounding the brain and within the ventricles), GM and WM this estimate shows an acceptable stability. By this supervised approach a high flexibility and precision for the segmentation of normal and pathologic brains is gained. The precision of this approach is shown using the Montreal brain phantom. Real data applications exemplify the advantage of the GM based approach, compared to the usual WM homogenization, allowing improved cortex segmentation

Dipolar modulation in number counts of WISE-2MASS sources

We test the statistical isotropy of the universe by analyzing the distribution of WISE extragalactic sources that were also observed by 2MASS. We pay particular attention to color cuts and foreground marginalization in order to cull a uniform sample of extragalactic objects and avoid stars. We detect a dipole gradient in the number-counts with an amplitude of $\sim$0.05, somewhat larger than expectations based on local structures corresponding to the depth and (independently measured) bias of our WISE-2MASS sources. The direction of the dipole, $(l,b)\simeq (310\,^{\circ}, -15\,^{\circ})$, is in reasonably good agreement with that found previously in the (shallower) 2MASS Extended Source Catalog alone. Interestingly, the dipole direction is not far from the direction of the dipolar modulation in the CMB found by Planck, and also fairly closely matches large-scale-structure bulk-flow directions found by various groups using galaxies and type Ia supernovae. It is difficult, however, to draw specific conclusions from the near-agreement of these directions.Comment: 5 pages, 3 figures. v2: extinction correction added; minor changes in result

Crustal interpretation of the MAGSAT data in the continental United States

The processing of MAGSAT scalar data to construct a crustal magnetic anomaly map over the continental U.S. involves removal of the reference field model, a path-by-path subtraction of a low order polynomial through a least-squares fit to reduce orbital offset errors, and a two dimensional spectral filtering to mitigate the spectral bias induced by the path-by-path orbital correction scheme. The resultant anomaly map shows reasonably good correlations with an aeromagnetic map derived from the project MAGNET. Prominent satellite magnetic anomalies are identified in terms of geological provinces and age boundaries. An inversion method was applied to MAGSAT data which produces both the Curie depth topography and laterally varying magnetic susceptibility of the crust. A contoured Curie depth map thus derived shows general agreements with a crustal thickness map based on seismic data

Uncertainty Quantification of Future Design Rainfall Depths in Korea

One of the most common ways to investigate changes in future rainfall extremes is to use future rainfall data simulated by climate models with climate change scenarios. However, the projected future design rainfall intensity varies greatly depending on which climate model is applied. In this study, future rainfall Intensity???Duration???Frequency (IDF) curves are projected using various combinations of climate models. Future Ensemble Average (FEA) is calculated using a total of 16 design rainfall intensity ensembles, and uncertainty of FEA is quantified using the coefficient of variation of ensembles. The FEA and its uncertainty vary widely depending on how the climate model combination is constructed, and the uncertainty of the FEA depends heavily on the inclusion of specific climate model combinations at each site. In other words, we found that unconditionally using many ensemble members did not help to reduce the uncertainty of future IDF curves. Finally, a method for constructing ensemble members that reduces the uncertainty of future IDF curves is proposed, which will contribute to minimizing confusion among policy makers in developing climate change adaptation policies

Biased-estimations of the Variance and Skewness

Nonlinear combinations of direct observables are often used to estimate quantities of theoretical interest. Without sufficient caution, this could lead to biased estimations. An example of great interest is the skewness $S_3$ of the galaxy distribution, defined as the ratio of the third moment \xibar_3 and the variance squared \xibar_2^2. Suppose one is given unbiased estimators for \xibar_3 and \xibar_2^2 respectively, taking a ratio of the two does not necessarily result in an unbiased estimator of $S_3$. Exactly such an estimation-bias affects most existing measurements of $S_3$. Furthermore, common estimators for \xibar_3 and \xibar_2 suffer also from this kind of estimation-bias themselves: for \xibar_2, it is equivalent to what is commonly known as the integral constraint. We present a unifying treatment allowing all these estimation-biases to be calculated analytically. They are in general negative, and decrease in significance as the survey volume increases, for a given smoothing scale. We present a re-analysis of some existing measurements of the variance and skewness and show that most of the well-known systematic discrepancies between surveys with similar selection criteria, but different sizes, can be attributed to the volume-dependent estimation-biases. This affects the inference of the galaxy-bias(es) from these surveys. Our methodology can be adapted to measurements of analogous quantities in quasar spectra and weak-lensing maps. We suggest methods to reduce the above estimation-biases, and point out other examples in LSS studies which might suffer from the same type of a nonlinear-estimation-bias.Comment: 28 pages of text, 9 ps figures, submitted to Ap

Rainfall frequency analysis for ungauged regions using remotely sensed precipitation information

Rainfall frequency analysis, which is an important tool in hydrologic engineering, has been traditionally performed using information from gauge observations. This approach has proven to be a useful tool in planning and design for the regions where sufficient observational data are available. However, in many parts of the world where ground-based observations are sparse and limited in length, the effectiveness of statistical methods for such applications is highly limited. The sparse gauge networks over those regions, especially over remote areas and high-elevation regions, cannot represent the spatiotemporal variability of extreme rainfall events and hence preclude developing depth-duration-frequency curves (DDF) for rainfall frequency analysis. In this study, the PERSIANN-CDR dataset is used to propose a mechanism, by which satellite precipitation information could be used for rainfall frequency analysis and development of DDF curves. In the proposed framework, we first adjust the extreme precipitation time series estimated by PERSIANN-CDR using an elevation-based correction function, then use the adjusted dataset to develop DDF curves. As a proof of concept, we have implemented our proposed approach in 20 river basins in the United States with different climatic conditions and elevations. Bias adjustment results indicate that the correction model can significantly reduce the biases in PERSIANN-CDR estimates of annual maximum series, especially for high elevation regions. Comparison of the extracted DDF curves from both the original and adjusted PERSIANN-CDR data with the reported DDF curves from NOAA Atlas 14 shows that the extreme percentiles from the corrected PERSIANN-CDR are consistently closer to the gauge-based estimates at the tested basins. The median relative errors of the frequency estimates at the studied basins were less than 20% in most cases. Our proposed framework has the potential for constructing DDF curves for regions with limited or sparse gauge-based observations using remotely sensed precipitation information, and the spatiotemporal resolution of the adjusted PERSIANN-CDR data provides valuable information for various applications in remote and high elevation areas

Constraining Stellar Feedback: Shock-ionized Gas in Nearby Starburst Galaxies

(abridged) We investigate the properties of feedback-driven shocks in 8 nearby starburst galaxies using narrow-band imaging data from the Hubble Space Telescope (HST). We identify the shock--ionized component via the line diagnostic diagram \oiii/\hb vs. \sii (or \nii)/\ha, applied to resolved regions 3--15 pc in size. We divide our sample into three sub-samples: sub-solar (Holmberg II, NGC 1569, NGC 4214, NGC 4449, and NGC 5253), solar (He 2-10, NGC 3077) and super-solar (NGC 5236) for consistent shock measurements. For the sub-solar sub-sample, we derive three scaling relations: (1) $L_{shock} \propto {SFR}^{~0.62}$, (2) $L_{shock} \propto {\Sigma_{SFR,HL}}^{~0.92}$, and (3) $L_{shock}/L_{tot} \propto {(L_H/L_{\odot,H})}^{-0.65}$, where $L_{shock}$ is the \ha luminosity from shock--ionized gas, ${\Sigma_{SFR,HL}}$ the SFR per unit half-light area, $L_{tot}$ the total \ha luminosity, and $L_H/L_{\odot,H}$ the absolute H-band luminosity from 2MASS normalized to solar luminosity. The other two sub--samples do not have enough number statistics, but appear to follow the first scaling relation. The energy recovered indicates that the shocks from stellar feedback in our sample galaxies are fully radiative. If the scaling relations are applicable in general to stellar feedback, our results are similar to those by Hopkins et al. (2012) for galactic super winds. This similarity should, however, be taken with caution at this point, as the underlying physics that enables the transition from radiative shocks to gas outflows in galaxies is still poorly understood.Comment: 29 pages, 14 figures, accepted for publication in the Ap

Analytic Scattering and Refraction Models for Exoplanet Transit Spectra

Observations of exoplanet transit spectra are essential to understanding the physics and chemistry of distant worlds. The effects of opacity sources and many physical processes combine to set the shape of a transit spectrum. Two such key processes - refraction and cloud and/or haze forward scattering - have seen substantial recent study. However, models of these processes are typically complex, which prevents their incorporation into observational analyses and standard transit spectrum tools. In this work, we develop analytic expressions that allow for the efficient parameterization of forward scattering and refraction effects in transit spectra. We derive an effective slant optical depth that includes a correction for forward scattered light, and present an analytic form of this correction. We validate our correction against a full-physics transit spectrum model that includes scattering, and we explore the extent to which the omission of forward scattering effects may bias models. Also, we verify a common analytic expression for the location of a refractive boundary, which we express in terms of the maximum pressure probed in a transit spectrum. This expression is designed to be easily incorporated into existing tools, and we discuss how the detection of a refractive boundary could help indicate the background atmospheric composition by constraining the bulk refractivity of the atmosphere. Finally, we show that opacity from Rayleigh scattering and collision induced absorption will outweigh the effects of refraction for Jupiter-like atmospheres whose equilibrium temperatures are above 400-500 K.Comment: ApJ accepted; submitted Feb. 7, 201

The APM Galaxy Survey III: An Analysis of Systematic Errors in the Angular Correlation Function and Cosmological Implications

We present measurements of the angular two-point galaxy correlation function, $w(theta)$, from the APM Galaxy Survey. The performance of various estimators of $w$ is assessed using simulated galaxy catalogues and analytic arguments. Several error analyses show that residual plate-to-plate errors do not bias our estimates of $w$ by more than $10^{-3}$. Direct comparison between our photometry and external CCD photometry of over 13,000 galaxies from the Las Campanas Deep Redshift Survey shows that the rms error in the APM plate zero points lies in the range 0.04-0.05 magnitudes, in agreement with our previous estimates. We estimate the effects on $w$ of atmospheric extinction and obscuration by dust in our Galaxy and conclude that these are negligible. We use our best estimates of the systematic errors in the survey to calculate corrected estimates of $w$. Deep redshift surveys are used to determine the selection function of the APM Galaxy Survey, and this is applied in Limber's equation to compute how $w$ scales as a function of limiting magnitude. Our estimates of $w$ are in excellent agreement with the scaling relation, providing further evidence that systematic errors in the APM survey are small. We explicitly remove large-scale structure by applying filters to the APM galaxy maps and conclude that there is still strong evidence for more clustering at large scales than predicted by the standard scale-invariant cold dark matter (CDM) model. We compare the APM $w$ and the three dimensional power spectrum derived by inverting $w$, with the predictions of scale-invariant CDM models. We show that the observations require $Gamma=Omega_0 h$ in the range 0.2-0.3 and are incompatible with the value $Gamma=0.5$ of the standard CDM model.Comment: 102 pages, plain TeX plus 41 postscript figures. Submitted to MNRA

Analysis of Satellite-to-Satellite Tracking (SST) and altimetry data from GEOS-C

Radar altimetry and satellite-to-satellite (SST) range and range rate tracking measurements were used to infer the exterior gravitational field of the earth and the structure of the geoid from GEOS-C metric data. Under the SST analysis, a direct point-by-point estimate of gravity disturbance by means of a recursive filter with backward smoothing was attempted but had to be forsaken because of poor convergence. The adopted representation consists of a more or less uniform grid of discrete masses at a depth of approximately 400 km from the earth's surface. The layer is superimposed on a spherical harmonics model. The procedure for smoothing the altimetry and inferring the fine-structured gravity field over the Atlantic test area is described. The local disturbances are represented by means of a density layer. The altimeter height biases were first estimated by a least squares adjustment at orbital crossover points. After taking out the bias, long wavelength contributions from GEM-6 as well as a calibration correction were subtracted. The residual heights were then represented by a mass distribution beneath the earth's surface