Adaptive image compression algorithm for angiograms stored on optical memory card

The main objective of the Cardio-Média project is to produce a coronarian multimedia data record stored on an optical car d in order to offer a better follow-up for the patients treated by angioplasty . In this paper, we present the compression algorithm implemented to store the angiographìc images of the data record . This algorithm is based on a wavelet decomposition followe d by an adapted lattice quantization of the wavelet coefficients . An original bit allocation algorithm is used during a learning step i n orderto provide a fast coding algorithm which is adapted to the angiographic images . A subjective evaluation of the diagnosti c quality of the images, based on the consensus approach leads to a compression ratio of 12 :1 which insures both a sufficien t medical quality and a sufficient data compression in regards to the storage capacity of the optical card .Le projet Cardio-Média a pour objectif la création d'un prototype de dossier coronarien sur carte optique afin de faciliter le suivi clinique des patients traités par angioplastie. Dans cet article, nous présentons l'algorithme de compression mis en oeuvre et les résultats obtenus. Notre algorithme utilise une transformation en ondelettes et une quantification vectorielle adaptée des coefficients d'ondelettes. Son originalité repose sur la phase d'apprentissage qui permet de disposer d'un algorithme de compression/décompression rapide adapté à la modalité médicale « angiographie ». Une évaluation subjective par consensus de la qualité diagnostique des images comprimées a permis de retenir un taux de compression de 12 qui répond aux contraintes matérielles et médicales du projet

Stress transfer and connectivity between the Bhutan Himalaya and the Shillong Plateau

International audienceWithin the northern Indian Plate, the Shillong Plateau is a peculiar geodynamic terrane, hosting significant seismic activity outboard the Himalayan belt. This activity is often used as an argument to explain apparent reduced seismicity in the Bhutan Himalayas. Although current geophysical and geodetic data indicate that the Bhutan Himalayas accommodate more deformation than the Shillong Plateau, we aim to quantify the extent to which the two geodynamic regimes are connected and potentially interact through stress transfers. We compiled a map of major faults and earthquakes in the two regions and computed co-seismic stress transfer amplitudes. Our results indicate that the Bhutan Himalayas and the Shillong Plateau are less connected than previously suggested. Major earthquakes in either of the two regions mainly affect transverse faults connecting them, causing up to ~40 bar Coulomb stress change; however, this effect is clearly less on thrust faults of the either region (up to 1 bar only). The MW 8.25 1897 Assam earthquake that affected the Shillong Plateau did not cause a stress shadow on the Main Himalayan Thrust in Bhutan as previously suggested. Similarly, the Mw 8 ± 0.5 1714 Bhutan earthquake had negligible impact on stress accumulation on thrust faults bounding the Shillong Plateau. Furthermore, the main process shaping the regional stress patterns continues to be interseismic loading with complex boundary conditions in a diffuse deformation field involving the Bengal Basin and Indo-Burman Ranges. While both the Bhutan Himalayas and the Shillong Plateau exhibit a compressional regime, their stress evolutions are more weakly connected than hypothesized. Although our modelling suggests lateral increase in stress interactions, from west (less) to east (more), in the Bhutan Himalayas, a clearer picture will only emerge with better constrained fault geometries, slip rates, crustal structure, and seismicity catalogues in the entire region of distributed deformation

A cross-center smoothness prior for variational Bayesian brain tissue segmentation

Suppose one is faced with the challenge of tissue segmentation in MR images, without annotators at their center to provide labeled training data. One option is to go to another medical center for a trained classifier. Sadly, tissue classifiers do not generalize well across centers due to voxel intensity shifts caused by center-specific acquisition protocols. However, certain aspects of segmentations, such as spatial smoothness, remain relatively consistent and can be learned separately. Here we present a smoothness prior that is fit to segmentations produced at another medical center. This informative prior is presented to an unsupervised Bayesian model. The model clusters the voxel intensities, such that it produces segmentations that are similarly smooth to those of the other medical center. In addition, the unsupervised Bayesian model is extended to a semi-supervised variant, which needs no visual interpretation of clusters into tissues.Comment: 12 pages, 2 figures, 1 table. Accepted to the International Conference on Information Processing in Medical Imaging (2019

Rate of Iceland Sea acidification from time series measurements

The Iceland Sea is one part of the Nordic Seas. Cold Arctic Water prevails there and the deep-water is an important source of North Atlantic Deep Water. We have evaluated time series observations of measured <i>p</i>CO<sub>2</sub> and total CO<sub>2</sub> concentration from discrete seawater samples during 1985–2008 for the surface and 1994–2008 for deep-water, and following changes in response to increasing atmospheric carbon dioxide. The surface pH in winter decreases at a rate of 0.0024 yr<sup>−1</sup>, which is 50% faster than average yearly rates at two subtropical time series stations, BATS and ESTOC. In the deep-water regime (>1500 m), the rate of pH decline is a quarter of that observed in surface waters. The surface seawater carbonate saturation states (Ω) are about 1.5 for aragonite and 2.5 for calcite, about half of levels found in subtropical surface waters. During 1985–2008, the degree of saturation (Ω) decreased at an average rate of 0.0072 yr<sup>−1</sup> for aragonite and 0.012 yr<sup>−1</sup> for calcite. The aragonite saturation horizon is currently at 1710 m and shoaling at 4 m yr<sup>−1</sup>. Based on this rate of shoaling and on the local hypsography, each year another 800 km<sup>2</sup> of seafloor becomes exposed to waters that have become undersaturated with respect to aragonite

Multi-modality image simulation with the Virtual Imaging Platform: Illustration on cardiac echography and MRI

International audienceMedical image simulation is useful for biological modeling, image analysis, and designing new imaging devices but it is not widely available due to the complexity of simulators, the scarcity of object models, and the heaviness of the associated computations. This paper presents the Virtual Imaging Platform, an openly-accessible web platform for multi-modality image simulation. The integration of simulators and models is described and exemplified on simulated cardiac MRIs and ultrasonic images

Global Carbon Budget 2020

Accurate assessment of anthropogenic carbon dioxide (CO$_{2}$) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO$_{2}$ emissions (E$_{FOS}$) are based on energy statistics and cement production data, while emissions from land-use change (E$_{LUC}$), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO$_{2}$ concentration is measured directly and its growth rate (G$_{ATM}$) is computed from the annual changes in concentration. The ocean CO$_{2}$ sink (S$_{OCEAN}$) and terrestrial CO$_{2}$ sink (S$_{LAND}$) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (B$_{IM}$), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2010–2019), E$_{FOS}$ was 9.6 ± 0.5 GtC yr$^{-1}$ excluding the cement carbonation sink (9.4 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and E$_{LUC}$ was 1.6 ± 0.7 GtC yr$^{-1}$. For the same decade, G$_{ATM}$ was 5.1 ± 0.02 GtC yr$^{-1}$ (2.4 ± 0.01 ppm yr$_{-1}$), S$_{OCEAN}$ 2.5 ±  0.6 GtC yr$^{-1}$, and S$_{LAND}$ 3.4 ± 0.9 GtC yr$^{-1}$, with a budget imbalance B$_{IM}$ of −0.1 GtC yr$^{-1}$ indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in E$_{FOS}$ was only about 0.1 % with fossil emissions increasing to 9.9 ± 0.5 GtC yr$^{-1}$ excluding the cement carbonation sink (9.7 ± 0.5 GtC yr$^{-1}$ when cement carbonation sink is included), and E$_{LUC}$ was 1.8 ± 0.7 GtC yr$^{-1}$, for total anthropogenic CO$_{2}$ emissions of 11.5 ± 0.9 GtC yr$^{-1}$ (42.2 ± 3.3 GtCO$_{2}$). Also for 2019, G$_{ATM}$ was 5.4 ± 0.2 GtC yr$^{-1}$ (2.5 ± 0.1 ppm yr$^{-1}$), S$_{OCEAN}$ was 2.6 ± 0.6 GtC yr$^{-1}$, and S$_{LAND}$ was 3.1 ± 1.2 GtC yr$^{-1}$, with a B$_{IM}$ of 0.3 GtC. The global atmospheric CO$_{2}$ concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in E$_{FOS}$ relative to 2019 of about −7 % (median estimate) based on individual estimates from four studies of −6 %, −7 %, −7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr$^{-1}$ persist for the representation of semi-decadal variability in CO$_{2}$ fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in the mean and trend in land-use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO$_{2}$ flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020)

Global Carbon Budget 2020

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2010–2019), EFOS was 9.6 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.4 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.6 ± 0.7 GtC yr−1. For the same decade, GATM was 5.1 ± 0.02 GtC yr−1 (2.4 ± 0.01 ppm yr−1), SOCEAN 2.5 ±  0.6 GtC yr−1, and SLAND 3.4 ± 0.9 GtC yr−1, with a budget imbalance BIM of −0.1 GtC yr−1 indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in EFOS was only about 0.1 % with fossil emissions increasing to 9.9 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.7 ± 0.5 GtC yr−1 when cement carbonation sink is included), and ELUC was 1.8 ± 0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5 ± 0.9 GtC yr−1 (42.2 ± 3.3 GtCO2). Also for 2019, GATM was 5.4 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.6 ± 0.6 GtC yr−1, and SLAND was 3.1 ± 1.2 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in EFOS relative to 2019 of about −7 % (median estimate) based on individual estimates from four studies of −6 %, −7 %, −7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in the mean and trend in land-use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020)

Quantitative study of the signal decay due to magnetic susceptibility interfaces: MRI simulations and experiments

In MRI, characterization of magnetic susceptibility artifacts can be necessary in a wide range of studies. We used both experience on a 0.2T magnet and MRI simulations to assess the signal decay over echo time at different pixel sizes in the case of air-water interfaces. The particular experimental signal modulation, reproduced in simulation, was clarified. Concordance between simulation and experience will enable further studies of magnetic susceptibility effects with more complex objects like in molecular imaging or in porous media imaging

Characterization of signal loss due to magnetic susceptibility interfaces in gradient-echo imaging by simulation and experiments

Magnetic susceptibility interfaces result in signal loss in gradient-echo MR images. The characterization of these susceptibility artefacts can be of greater importance in number of studies such as paramagnetic markers tracking, BOLD imaging or porous media analyses. We are interested in the signal decay at different pixel sizes in the case of an air-water interface in 2D GE imaging. We used both experience on a 0.2T magnet and MRI simulation to assess the signals behaviours

The Irminger Sea and the Iceland Sea time series measurements of sea water carbon and nutrient chemistry 1983–2008

This paper describes the ways and means of assembling and quality controling the Irminger Sea and Iceland Sea time-series biogeochemical data which are included in the CARINA data set. The Irminger Sea and the Iceland Sea are hydrographically different regions where measurements of sea water carbon and nutrient chemistry were started in 1983. The sampling is seasonal, four times a year. The carbon chemistry is studied with measurements of the partial pressure of carbon dioxide in seawater, <i>p</i>CO<sub>2</sub>, and total dissolved inorganic carbon, TCO<sub>2</sub>. The carbon chemistry data are for surface waters only until 1991 when water column sampling was initiated. Other measured parameters are salinity, dissolved oxygen and the inorganic nutrients nitrate, phosphate and silicate. Because of the CARINA criteria for secondary quality control, depth >1500 m, the IRM-TS could not be included in the routine QC and the IS-TS only in a limited way. However, with the information provided here, the quality of the data can be assessed, e.g. on the basis of the results obtained with the use of reference materials