Spectrophotometric properties of the nucleus of comet 67P/Churyumov-Gerasimenko from the OSIRIS instrument onboard the ROSETTA spacecraft

Context. The Rosetta mission of the European Space Agency has been orbiting the comet 67P/Churyumov-Gerasimenko (67P) since August 2014 and is now in its escort phase. A large complement of scientific experiments designed to complete the most detailed study of a comet ever attempted are onboard Rosetta. Aims. We present results for the photometric and spectrophotometric properties of the nucleus of 67P derived from the OSIRIS imaging system, which consists of a Wide Angle Camera (WAC) and a Narrow Angle Camera (NAC). The observations presented here were performed during July and the beginning of August 2014, during the approach phase, when OSIRIS was mapping the surface of the comet with several filters at different phase angles (1.3 degrees-54 degrees). The resolution reached up to 2.1 m/px. Methods. The OSIRIS images were processed with the OSIRIS standard pipeline, then converted into I/F. radiance factors and corrected for the illumination conditions at each pixel using the Lommel-Seeliger disk law. Color cubes of the surface were produced by stacking registered and illumination-corrected images. Furthermore, photometric analysis was performed both on disk-averaged photometry in several filters and on disk-resolved images acquired with the NAC orange filter, centered at 649 ran, using Hapke modeling. Results. The disk-averaged phase function of the nucleus of 67P shows a strong opposition surge with a G parameter value of -0.13 +/- 0.01 in the HG system formalism and an absolute magnitude H-v(1, 1, 0) = 15.74 +/- 0.02 mag. The integrated spectrophotometry in 20 filters covering the 250-1000 nm wavelength range shows a red spectral behavior, without clear absorption bands except for a potential absorption centered at similar to 290 rim that is possibly due to SO2 ice. The nucleus shows strong phase reddening, with disk-averaged spectral slopes increasing from 11%/( 100 nm) to 16%/(100 nm) in the 1.3 degrees-54 degrees phase angle range. The geometric albedo of the comet is 6.5 +/- 0.2% at 649 nm, with local variations of up to similar to 16% in the Hapi region. From the disk-resolved images we computed the spectral slope together with local spectrophotometry and identified three distinct groups of regions (blue, moderately red, and red). The Hapi region is the brightest, the bluest in term of spectral slope, and the most active surface on the comet. Local spectrophotometry shows an enhancement of the flux in the 700-750 nm that is associated with coma emissions.

STUDY OF THE EFFECTS OF TOTAL MODULATION TRANSFER FUNCTION CHANGES ON OBSERVER PERFORMANCE USING CLINICAL MAMMOGRAMS

The main goal of this study was to relate physical changes in image quality measured by Modulation Transfer Function (MTF) to diagnostic accuracy.^ One Hundred and Fifty Kodak Min-R screen/film combination conventional craniocaudal mammograms obtained with the Pfizer Microfocus Mammographic system were selected from the files of the Department of Radiology, at M.D. Anderson Hospital and Tumor Institute.^ The mammograms included 88 cases with a variety of benign diagnosis and 62 cases with a variety of malignant biopsy diagnosis. The average age of the patient population was 55 years old. 70 cases presented calcifications with 30 cases having calcifications smaller than 0.5mm. 46 cases presented irregular bordered masses larger than 1 cm. 30 cases presented smooth bordered masses with 20 larger than 1 cm.^ Four separated copies of the original images were made each having a different change in the MTF using a defocusing technique whereby copies of the original were obtained by light exposure through different thicknesses (spacing) of transparent film base.^ The mammograms were randomized, and evaluated by three experienced mammographers for the degree of visibility of various anatomical breast structures and pathological lesions (masses and calicifications), subjective image quality, and mammographic interpretation.^ 3,000 separate evaluations were anayzed by several statistical techniques including Receiver Operating Characteristic curve analysis, McNemar test for differences between proportions and the Landis et al. method of agreement weighted kappa for ordinal categorical data.^ Results from the statistical analysis show: (1) There were no statistical significant differences in the diagnostic accuracy of the observers when diagnosing from mammograms with the same MTF. (2) There were no statistically significant differences in diagnostic accuracy for each observer when diagnosing from mammograms with the different MTF's used in the study. (3) There statistical significant differences in detail visibility between the copies and the originals. Detail visibility was better in the originals. (4) Feature interpretations were not significantly different between the originals and the copies. (5) Perception of image quality did not affect image interpretation.^ Continuation and improvement of this research ca be accomplished by: using a case population more sensitive to MTF changes, i.e., asymptomatic women with minimum breast cancer, more observers (including less experienced radiologists and experienced technologists) must collaborate in the study, and using a minimum of 200 benign and 200 malignant cases.^

Mineralogical and stable isotope analyses of carbonates from the eastern Black Sea

Authigenic carbonates associated with cold seeps provide valuable archives of changes in the long-term seepage activity. To investigate the role of shallow-buried hydrates on the seepage strength and fluid composition we analysed methane-derived carbonate precipitates from a high-flux hydrocarbon seepage area ("Batumi seep area") located on the south-eastern Black Sea slope in ca. 850 m. In a novel approach, we combined computerized X-ray tomography (CT) with mineralogical and isotope geochemical methods to get additional insights into the three-dimensional internal structure of the carbonate build-ups. X-ray diffractometry revealed the presence of two different authigenic carbonate phases, i.e. pure aragonitic rims associated with vital microbial mats and high-Mg calcite cementing the hemipelagic sediment. As indicated by the CT images, the initial sediment has been strongly deformed, first plastic then brittle, leading to brecciation of the progressively cemented sediment. The aragonitic rims on the other hand, represent a presumably recent carbonate growth phase since they cover the already deformed sediment. The stable oxygen isotope signature indicates that the high-Mg calcite cement incorporated pore water mixed with substantial hydrate water amounts. This points at a dominant role of high gas/fluid flux from decomposing gas hydrates leading to the deformation and cementation of the overlying sediment. In contrast, the aragonitic rims do not show an influence of 18O-enriched hydrate water. The differences in d18O between the presumably recent aragonite precipitates and the older high-Mg cements suggest that periods of hydrate dissociation and vigorous fluid discharge alternated with times of hydrate stability and moderate fluid flow. These results indicate that shallow-buried gas hydrates are prone to episodic decomposition with associated vigorous fluid flow. This might have a profound impact on the seafloor morphology resulting e.g. in the formation of carbonate pavements and pockmark-like structures but might also affect the local carbon cycle.

Building the View Graph of a Category by Exploiting Image Realism

We propose a weakly supervised method to arrange images of a given category based on the relative pose between the camera and the object in the scene. Relative poses are points on a sphere centered at the object in a given canonical pose, which we call object viewpoints. Our method builds a graph on this sphere by assigning images with similar viewpoint to the same node and by connecting nodes if they are related by a small rotation. The key idea is to exploit a large unlabeled dataset to validate the likelihood of dominant 3D planes of the object geometry. A number of 3D plane hypotheses are evaluated by applying small 3D rotations to each hypothesis and by measuring how well the deformed images match other images in the dataset. Correct hypotheses will result in deformed images that correspond to plausible views of the object, and thus will likely match well other images in the same category. The identified 3D planes are then used to compute affinities between images related by a change of viewpoint. We then use the affinities to build a view graph via a greedy method and the maximum spanning tree.

Toward reduction of artifacts in fused images

Most fusion satellite image methodologies at pixel-level introduce false spatial details, i.e.artifacts, in the resulting fusedimages. In many cases, these artifacts appears because image fusion methods do not consider the differences in roughness or textural characteristics between different land covers. They only consider the digital values associated with single pixels. This effect increases as the spatial resolution image increases. To minimize this problem, we propose a new paradigm based on local measurements of the fractal dimension (FD). Fractal dimension maps (FDMs) are generated for each of the source images (panchromatic and each band of the multi-spectral images) with the box-counting algorithm and by applying a windowing process. The average of source image FDMs, previously indexed between 0 and 1, has been used for discrimination of different land covers present in satellite images. This paradigm has been applied through the fusion methodology based on the discrete wavelet transform (DWT), using the à trous algorithm (WAT). Two different scenes registered by optical sensors on board FORMOSAT-2 and IKONOS satellites were used to study the behaviour of the proposed methodology. The implementation of this approach, using the WAT method, allows adapting the fusion process to the roughness and shape of the regions present in the image to be fused. This improves the quality of the fusedimages and their classification results when compared with the original WAT method

Analysis of Thematic Classified Aerial Images Trough Multispectral and LIDAR Data

The application of thematic maps obtained through the classification of remote images needs the obtained products with an optimal accuracy. The registered images from the airplanes display a very satisfactory spatial resolution, but the classical methods of thematic classification not always give better results than when the registered data from satellite are used. In order to improve these results of classification, in this work, the LIDAR sensor data from first return (Light Detection And Ranging) registered simultaneously with the spectral sensor data from airborne are jointly used. The final results of the thematic classification of the scene object of study have been obtained, quantified and discussed with and without LIDAR data, after applying different methods: Maximum Likehood Classification, Support Vector Machine with four different functions kernel and Isodata clustering algorithm (ML, SVM-L, SVM-P, SVM-RBF, SVM-S, Isodata). The best results are obtained for SVM with Sigmoide kernel. These allow the correlation with others different physical parameters with great interest like Manning hydraulic coefficient, for their incorporation in a GIS and their application in hydraulic modeling.

Experimental analysis of the breakage of a liquid bridge under microgravity conditions

The experimental results obtained in experiment “STACO” made on board the Spacelab D-2 are re-visited, with image-analysis tools not then available. The configuration consisted of a liquid bridge between two solid supporting discs. An expected breakage occurred during the experiment. The recorded images are analysed and the measured behaviour compared with the results of a three dimensional model of the liquid dynamics, obtaining a much better fit than with linear models

Crowdsourcing malaria parasite quantification: an online game for analyzing images of infected thick blood smears

Background: There are 600,000 new malaria cases daily worldwide. The gold standard for estimating the parasite burden and the corresponding severity of the disease consists in manually counting the number of parasites in blood smears through a microscope, a process that can take more than 20 minutes of an expert microscopist’s time. Objective: This research tests the feasibility of a crowdsourced approach to malaria image analysis. In particular, we investigated whether anonymous volunteers with no prior experience would be able to count malaria parasites in digitized images of thick blood smears by playing a Web-based game. Methods: The experimental system consisted of a Web-based game where online volunteers were tasked with detecting parasites in digitized blood sample images coupled with a decision algorithm that combined the analyses from several players to produce an improved collective detection outcome. Data were collected through the MalariaSpot website. Random images of thick blood films containing Plasmodium falciparum at medium to low parasitemias, acquired by conventional optical microscopy, were presented to players. In the game, players had to find and tag as many parasites as possible in 1 minute. In the event that players found all the parasites present in the image, they were presented with a new image. In order to combine the choices of different players into a single crowd decision, we implemented an image processing pipeline and a quorum algorithm that judged a parasite tagged when a group of players agreed on its position. Results: Over 1 month, anonymous players from 95 countries played more than 12,000 games and generated a database of more than 270,000 clicks on the test images. Results revealed that combining 22 games from nonexpert players achieved a parasite counting accuracy higher than 99%. This performance could be obtained also by combining 13 games from players trained for 1 minute. Exhaustive computations measured the parasite counting accuracy for all players as a function of the number of games considered and the experience of the players. In addition, we propose a mathematical equation that accurately models the collective parasite counting performance. Conclusions: This research validates the online gaming approach for crowdsourced counting of malaria parasites in images of thick blood films. The findings support the conclusion that nonexperts are able to rapidly learn how to identify the typical features of malaria parasites in digitized thick blood samples and that combining the analyses of several users provides similar parasite counting accuracy rates as those of expert microscopists. This experiment illustrates the potential of the crowdsourced gaming approach for performing routine malaria parasite quantification, and more generally for solving biomedical image analysis problems, with future potential for telediagnosis related to global health challenges.

Application of Independent Components Analysis with the JADE algorithm and NIR hyperspectral imaging for revealing food adulteration

In recent years, Independent Components Analysis (ICA) has proven itself to be a powerful signal-processing technique for solving the Blind-Source Separation (BSS) problems in different scientific domains. In the present work, an application of ICA for processing NIR hyperspectral images to detect traces of peanut in wheat flour is presented. Processing was performed without a priori knowledge of the chemical composition of the two food materials. The aim was to extract the source signals of the different chemical components from the initial data set and to use them in order to determine the distribution of peanut traces in the hyperspectral images. To determine the optimal number of independent component to be extracted, the Random ICA by blocks method was used. This method is based on the repeated calculation of several models using an increasing number of independent components after randomly segmenting the matrix data into two blocks and then calculating the correlations between the signals extracted from the two blocks. The extracted ICA signals were interpreted and their ability to classify peanut and wheat flour was studied. Finally, all the extracted ICs were used to construct a single synthetic signal that could be used directly with the hyperspectral images to enhance the contrast between the peanut and the wheat flours in a real multi-use industrial environment. Furthermore, feature extraction methods (connected components labelling algorithm followed by flood fill method to extract object contours) were applied in order to target the spatial location of the presence of peanut traces. A good visualization of the distributions of peanut traces was thus obtained

Invariance of brain-wave representations of simple visual images and their names

In two experiments, electric brain waves of 14 subjects were recorded under several different conditions to study the invariance of brain-wave representations of simple patches of colors and simple visual shapes and their names, the words blue, circle, etc. As in our earlier work, the analysis consisted of averaging over trials to create prototypes and test samples, to both of which Fourier transforms were applied, followed by filtering and an inverse transformation to the time domain. A least-squares criterion of fit between prototypes and test samples was used for classification. The most significant results were these. By averaging over different subjects, as well as trials, we created prototypes from brain waves evoked by simple visual images and test samples from brain waves evoked by auditory or visual words naming the visual images. We correctly recognized from 60% to 75% of the test-sample brain waves. The general conclusion is that simple shapes such as circles and single-color displays generate brain waves surprisingly similar to those generated by their verbal names. These results, taken together with extensive psychological studies of auditory and visual memory, strongly support the solution proposed for visual shapes, by Bishop Berkeley and David Hume in the 18th century, to the long-standing problem of how the mind represents simple abstract ideas.

Beautiful victims : childhood and the holocaust in the work of Gottfried Helnwein

"For the past three decades, contemporary artist Gottfried Helnwein has shocked viewers with his Holocaust-related paintings, drawings and installations. Born in Austria in 1948, Helnwein witnessed the immediate aftermath of World War II in Europe from a child’s perspective. Consequently, the horrifying images summoned from Helnwein’s imagination are inspired by the memories and repercussions of this tragedy. His work addresses his parents’ unwillingness to speak of the atrocities as well as the exploitation of the Holocaust in contemporary popular media. His work questions not only how such a tragedy could have taken place, but also how contemporary perception of this event has been affected by total media saturation and the passage of time. To shock viewers, Helnwein portrays strikingly realistic images of distressed, wounded and morally ambiguous children in works that have been regarded as controversial and outspoken"

Twenty-year advanced DInSAR analysis of severe land subsidence: The Alto Guadalentín Basin (Spain) case study

A twenty-year period of severe land subsidence evolution in the Alto Guadalentín Basin (southeast Spain) is monitored using multi-sensor SAR images, processed by advanced differential interferometric synthetic aperture radar (DInSAR) techniques. The SAR images used in this study consist of four datasets acquired by ERS-1/2, ENVISAT, ALOS and COSMO-SkyMed satellites between 1992 and 2012. The integration of ground surface displacement maps retrieved for different time periods allows us to quantify up to 2.50 m of cumulated displacements that occurred between 1992 and 2012 in the Alto Guadalentín Basin. DInSAR results were locally compared with global positioning system (GPS) data available for two continuous stations located in the study area, demonstrating the high consistency of local vertical motion measurements between the two different surveying techniques. An average absolute error of 4.6 ± 4 mm for the ALOS data and of 4.8 ± 3.5 mm for the COSMO-SkyMed data confirmed the reliability of the analysis. The spatial analysis of DInSAR ground surface displacement reveals a direct correlation with the thickness of the compressible alluvial deposits. Detected ground subsidence in the past 20 years is most likely a consequence of a 100–200 m groundwater level drop that has persisted since the 1970s due to the overexploitation of the Alto Guadalentín aquifer system. The negative gradient of the pore pressure is responsible for the extremely slow consolidation of a very thick (> 100 m) layer of fine-grained silt and clay layers with low vertical hydraulic permeability (approximately 50 mm/h) wherein the maximum settlement has still not been reached.

The fortunes and misfortunes of the famous Moll Flanders ... : written from her own memorandums.

The fortunes and misfortunes of the famous Moll Flanders -- Selected writings from Applebee's Journal -- The king of pirates, Captain Avery.

Computational methods for the detection of facial palsy

We are developing a telemedicine application which offers automated diagnosis of facial (Bell's) palsy through a Web service. We used a test data set of 43 images of facial palsy patients and 44 normal people to develop the automatic recognition algorithm. Three different image pre-processing methods were used. Machine learning techniques (support vector machine, SVM) were used to examine the difference between the two halves of the face. If there was a sufficient difference, then the SVM recognized facial palsy. Otherwise, if the halves were roughly symmetrical, the SVM classified the image as normal. It was found that the facial palsy images had a greater Hamming Distance than the normal images, indicating greater asymmetry. The median distance in the normal group was 331 (interquartile range 277-435) and the median distance in the facial palsy group was 509 (interquartile range 334-703). This difference was significant (P

Objective grading of the anterior eye

Purpose. To convert objective image analysis of anterior ocular surfaces into recognisable clinical grades, in order to provide a more sensitive and reliable equivalent to current subjective grading methods; a prospective, randomized study correlating clinical grading with digital image assessment. Methods. The possible range of clinical presentations Of bulbar and palpebral hyperaemia, palpebral roughness and corneal staining were represented by 4 sets of 10 images. The images were displayed in random order and graded by 50 clinicians using both subjective CCLRU and Efron grading scales. Previously validated objective image analysis was performed 3 times oil each of the 40 images. Digital measures included edge-detection and relative-coloration components. Step-wise regression analysis determined correlations between the average subjective grade and the objective image analysis measures. Results. Average subjective grades Could be predicted by a combination of the objective image analysis components. These digital ``grades'' accounted for between 69%, (for Efron scale-graded palpebral redness) and 98% (for Efron scale-graded bulbar hyperaemia) of the subjective variance. Conclusions. The results indicate that clinicians may use a combination of vessel areas and overall hue in their judgment of clinical severity for certain conditions. Objective grading call take these aspects into account, and be used to predict an average ``objective grade'' to be used by a clinician in describing the anterior eye. These measures are more sensitive and reliable than subjective grading while still utilizing familiar terminology, and can be applied in research or practice to improve the detection, and monitoring of ocular surface changes.