Real-time Tracking of Deformable Target in 3D Ultrasound Images

International audience— In this paper, we present a novel approach for tracking a deformable anatomical target within 3D ultrasound volumes. Our method is able to estimate deformations caused by the physiological motions of the patient. The displacements of moving structures are estimated from an intensity-based approach combined with a physically-based model and has therefore the advantage to be less sensitive to the image noise. Furthermore, our method does not use any fiducial marker and has real-time capabilities. The accuracy of our method is evaluated on real data acquired from an organic phantom. The validation is performed on different types of motions comprising rigid and non-rigid motions. Thus, our approach opens novel possibilities for computer-assisted interventions where deformable organs are involved

Interactive Tracking of Soft Tissues in 2D Ultrasound Images

SURGETICA 2014, Chambery, FranceIn several medical applications such as liver or kidney biopsies, an anatomical region needs to be continuously tracked during the intervention. When using ultrasound (US) image modality, tracking soft tissues remains challenging due to the deformations caused by physiological motions or medical instruments, combined with the generally weak quality of the images. In order to overcome the previous limitation, different techniques based on physical model have been proposed in the literature. [SMSM06] proposed a registration method based on the mass-spring system in order to constrain the deformation, and Zhang et al [ZW13] introduced an other registration technique based on finite element model where the extraction of the scale invariant features is needed. However, their model are built from features which are difficult to extract in US images due to the speckle noise. Finally, Marami et al [MSFC14] presented very recently an elastic registration method applicable to multi-modality image registration where the deformation is computed from modality independent neighborhood descriptor. In this paper, we propose an approach for tracking deformable target within 2D US images based on a physical model driven by smooth displacement field obtained from dense information. This allows to take into account highly localized deformation in the US images. Section 2 presents our method based on a combination of an intensity-based approach and a physically-based model. Section 3 describes the performances of our approach and comparisons on real data. Section 4 concludes the paper

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives