Abstract. Coronal Mass ejections (CMEs) are enormous eruptions of magnetized plasma expelled from the Sun into the interplanetary space, over the course of hours to days. They can create major disturbances in the interplanetary medium and trigger severe magnetic storms when they collide with the Earth's magnetosphere. It is important to know their real speed, propagation direction and 3-D configuration in order to accurately predict their arrival time at the Earth. Using data from the SECCHI coronagraphs onboard the STEREO mission, which was launched in October 2006, we can infer the propagation direction and the 3-D structure of such events. In this review, we first describe different techniques that were used to model the 3-D configuration of CMEs in the coronagraph field of view (up to 15 R ).Correspondence to: M. Mierla (mmierla@gmail.com) Then, we apply these techniques to different CMEs observed by various coronagraphs. A comparison of results obtained from the application of different reconstruction algorithms is presented and discussed.

We consider the probe of astrophysical signals through radio interferometers with small field of view and baselines with non-negligible and constant component in the pointing direction. In this context, the visibilities measured essentially identify with a noisy and incomplete Fourier coverage of the product of the planar signals with a linear chirp modulation. In light of the recent theory of compressed sensing and in the perspective of defining the best possible imaging techniques for sparse signals, we analyze the related spread spectrum phenomenon and suggest its universality relative to the sparsity dictionary. Our results rely both on theoretical considerations related to the mutual coherence between the sparsity and sensing dictionaries, as well as on numerical simulations.Comment: 10 pages, 3 figures. Version 2 matches version accepted for publication in MNRAS. Changes include minor clarification

This paper addresses the problem of localizing people in low and high density crowds with a network of heterogeneous cameras. The problem is recast as a linear inverse problem. It relies on deducing the discretized occupancy vector of people on the ground, from the noisy binary silhouettes observed as foreground pixels in each camera. This inverse problem is regularized by imposing a sparse occupancy vector, i.e., made of few non-zero elements, while a particular dictionary of silhouettes linearly maps these nonempty grid locations to the multiple silhouettes viewed by the cameras network. The proposed framework is (i) generic to any scene of people, i.e., people are located in low and high density crowds, (ii) scalable to any number of cameras and already working with a single camera, (iii) unconstrained by the scene surface to be monitored, and (iv) versatile with respect to the camera's geometry, e.g., planar or omnidirectional.Qualitative

Monte Carlo simulation (MCS) plays a key role in medical applications, especially for emission tomography and radiotherapy. However MCS is also associated with long calculation times that prevent its use in routine clinical practice. Recently, graphics processing units (GPU) became in many domains a low cost alternative for the acquisition of high computational power. The objective of this work was to develop an efficient framework for the implementation of MCS on GPU architectures. Geant4 was chosen as the MCS engine given the large variety of physics processes available for targeting different medical imaging and radiotherapy applications. In addition, Geant4 is the MCS engine behind GATE which is actually the most popular medical applications' simulation platform. We propose the definition of a global strategy and associated structures for such a GPU based simulation implementation. Different photon and electron physics effects are resolved on the fly directly on GPU without any approximations with respect to Geant4. Validations have shown equivalence in the underlying photon and electron physics processes between the Geant4 and the GPU codes with a speedup factor of 80-90. More clinically realistic simulations in emission and transmission imaging led to acceleration factors of 400-800 respectively compared to corresponding GATE simulations.

The LASCO-C2 coronagraph aboard the SOHO solar observatory has been providing a continuous flow of coronal images since 1996. Synoptic maps for each Carrington rotation have been built from these images, and offer a global view of the temporal evolution of the solar corona, particularly the occurrence of transient events. Coronal Mass Ejections (CMEs) present distinct signatures thus offering a novel approach to the problem of their identification and characterization. We present in this article an automated method of detection based on their morphological appearance on synoptic maps. It is based on adaptive filtering and segmentation, followed by merging with high-level knowledge. The program builds a catalog which lists the CMEs detected for each Carrington Rotation, together with their main estimated parameters: time of appearance, position angle, angular extent, average velocity and intensity. Our final catalog LASCO-ARTEMIS (Automatic Recognition of Transient Events and Marseille Inventory from Synoptic maps) is compared with existing catalogs, CDAW, CACTUS and SEEDS. We find that, likewise the automated CACTUS and SEEDS catalogs, we detect many more events than the CDAW catalog which is based on visual detection. The total number of detected CMEs strongly depends upon the sensitivity to small, faint and numerous events.Y. Boursier et al. Figure 1The last solar cycles illustrated by the monthly and smoothed variations of the sunspot number and the solar space missions (courtesy SIDC-team).

International audienceThe ARTEMIS-I catalog of coronal mass ejections (CMEs) was initially developed on a first generation of low-resolution synoptic maps constructed from the SOHO/LASCO-C2 images of the K-corona and resulted in an online database listing all events detected since January 1996 (Boursier et al., Solar Phys. 257, 125, 2009). A new generation of synoptic maps with higher temporal (a factor of 1.5) and angular (a factor of 2.5) resolutions allowed us to reconsider the question of CME detection and resulted in the production of a new catalog: ARTEMIS-II. The parameters estimated for each detected CME are still the date and time of appearance, the position angle, the angular width, and (when detected at several solar distances) the global and median velocities. The new synoptic maps correct for the limited number of velocity determinations reported in the ARTEMIS-I catalog. We now determine the propagation velocity of 79 % of detected CMEs instead of 30 % in the previous version. A final major improvement is the estimation of the mass and kinetic energy of all CMEs for which we could determine the velocity, that is a parts per thousand aEuro parts per thousand 13 000 CMEs until December 2010. Individual comparisons of velocity determination of 23 CMEs for which a full three-dimensional kinematical solution has been published indicate that ARTEMIS-II performs extremely well except at the highest velocities, an intrinsic limitation of our method. Finally, individual comparisons of mass determination of seven CMEs for which a robust solution has been obtained from stereographic observations demonstrate the quality of the ARTEMIS-II results

A generic approach is presented to detect and track people with a network of fixed and omnidirectional cameras given severely degraded foreground silhouettes. The problem is formulated as a sparsity constrained inverse problem. A dictionary made of atoms representing the silhouettes of a person at a given location is used within the problem formulation. A reweighted scheme is considered to better approximate the sparsity prior.Although the framework is generic to any scene, the focus of this paper is to evaluate the performance of the proposed approach on a basketball game. The main challenges come from the players' behavior, their similar appearance, and the mutual occlusions present in the views. In addition, the extracted foreground silhouettes are severely degraded due to the polished floor reflecting the players, and the strong shadow present in the scene. We present qualitative and quantitative results with the APIDIS dataset as part of the ICDSC sport challenge. 1

We propose a novel prompt-gamma (PG) imaging modality for real-time monitoring in proton therapy: PG time imaging (PGTI). By measuring the time-of-flight (TOF) between a beam monitor and a PG detector, our goal is to reconstruct the PG vertex distribution in 3D. In this paper, a dedicated, non-iterative reconstruction strategy is proposed (PGTI reconstruction). Here, it was resolved under a 1D approximation to measure a proton range shift along the beam direction. In order to show the potential of PGTI in the transverse plane, a second method, based on the calculation of the centre of gravity (COG) of the TIARA pixel detectors’ counts was also explored. The feasibility of PGTI was evaluated in two different scenarios. Under the assumption of a 100 ps (rms) time resolution (achievable in single proton regime), MC simulations showed that a millimetric proton range shift is detectable at 2σ with 108 incident protons in simplified simulation settings. With the same proton statistics, a potential 2 mm sensitivity (at 2σ with 108 incident protons) to beam displacements in the transverse plane was found using the COG method. This level of precision would allow to act in real-time if the treatment does not conform to the treatment plan. A worst case scenario of a 1 ns (rms) TOF resolution was also considered to demonstrate that a degraded timing information can be compensated by increasing the acquisition statistics: in this case, a 2 mm range shift would be detectable at 2σ with 109 incident protons. By showing the feasibility of a time-based algorithm for the reconstruction of the PG vertex distribution for a simplified anatomy, this work poses a theoretical basis for the future development of a PG imaging detector based on the measurement of particle TOF.