Characterization of retinal arteries by adaptive optics ophthalmoscopy image analysis.

OBJECTIVE: This paper aims at quantifying biomarkers from the segmentation of retinal arteries in adaptive optics ophthalmoscopy images (AOO). METHODS: The segmentation is based on the combination of deep learning and knowledge-driven deformable models to achieve a precise segmentation of the vessel walls, with a specific attention to bifurcations. Biomarkers (junction coefficient, branching coefficient, wall to lumen ratio (wlr) are derived from the resulting segmentation. RESULTS: reliable and accurate segmentations (mse = 1.75 ± 1.24 pixel) and measurements are obtained, with high reproducibility with respect to images acquisition and users, and without bias. SIGNIFICANCE: In a preliminary clinical study of patients with a genetic small vessel disease, some of them with vascular risk factors, an increased wlr was found in comparison to a control population. CONCLUSION: The wlr estimated in AOO images with our method (AOV, Adaptive Optics Vessel analysis) seems to be a very robust biomarker as long as the wall is well contrasted.

Fine-Structure Qubit Encoded in Metastable Strontium Trapped in an Optical Lattice.

We demonstrate coherent control of the fine-structure qubit in neutral strontium atoms. This qubit is encoded in the metastable ^{3}P_{2} and ^{3}P_{0} states, coupled by a Raman transition. Using a magnetic quadrupole transition, we demonstrate coherent state initialization of this THz qubit. We show Rabi oscillations with more than 60 coherent cycles and single-qubit rotations on the µs scale. With spin echo, we demonstrate coherence times of tens of ms. Our results pave the way for fast quantum information processors and highly tunable quantum simulators with two-electron atoms.

Equation of State and Thermometry of the 2D SU(N) Fermi-Hubbard Model.

We characterize the equation of state (EoS) of the SU(N>2) Fermi-Hubbard Model (FHM) in a two-dimensional single-layer square optical lattice. We probe the density and the site occupation probabilities as functions of interaction strength and temperature for N=3, 4, and 6. Our measurements are used as a benchmark for state-of-the-art numerical methods including determinantal quantum Monte Carlo and numerical linked cluster expansion. By probing the density fluctuations, we compare temperatures determined in a model-independent way by fitting measurements to numerically calculated EoS results, making this a particularly interesting new step in the exploration and characterization of the SU(N) FHM.

QFib: Fast and Efficient Brain Tractogram Compression.

Diffusion MRI fiber tracking datasets can contain millions of 3D streamlines, and their representation can weight tens of gigabytes of memory. These sets of streamlines are called tractograms and are often used for clinical operations or research. Their size makes them difficult to store, visualize, process or exchange over the network. We propose a new compression algorithm well-suited for tractograms, by taking advantage of the way streamlines are obtained with usual tracking algorithms. Our approach is based on unit vector quantization methods combined with a spatial transformation which results in low compression and decompression times, as well as a high compression ratio. For instance, a 11.5GB tractogram can be compressed to a 1.02GB file and decompressed in 11.3 seconds. Moreover, our method allows for the compression and decompression of individual streamlines, reducing the need for a costly out-of-core algorithm with heavy datasets. Last, we open a way toward on-the-fly compression and decompression for handling larger datasets without needing a load of RAM (i.e. in-core handling), faster network exchanges and faster loading times for visualization or processing.

State-Dependent Optical Lattices for the Strontium Optical Qubit.

We demonstrate state-dependent optical lattices for the Sr optical qubit at the tune-out wavelength for its ground state. We tightly trap excited state atoms while suppressing the effect of the lattice on ground state atoms by more than 4 orders of magnitude. This highly independent control over the qubit states removes inelastic excited state collisions as the main obstacle for quantum simulation and computation schemes based on the Sr optical qubit. Our results also reveal large discrepancies in the atomic data used to calibrate the largest systematic effect of Sr optical lattice clocks.

Observation of Coherent Multiorbital Polarons in a Two-Dimensional Fermi Gas.

We report on the experimental observation of multiorbital polarons in a two-dimensional Fermi gas of ^{173}Yb atoms formed by mobile impurities in the metastable ^{3}P_{0} orbital and a Fermi sea in the ground-state ^{1}S_{0} orbital. We spectroscopically probe the energies of attractive and repulsive polarons close to an orbital Feshbach resonance and characterize their coherence by measuring the quasiparticle residue. For all probed interaction parameters, the repulsive polaron is a long-lived quasiparticle with a decay rate more than 2 orders of magnitude below its energy. We formulate a many-body theory, which accurately treats the interorbital interactions in two dimensions and agrees well with the experimental results. Our work paves the way for the investigation of many-body physics in multiorbital ultracold Fermi gases.

Kidney cortex segmentation in 2D CT with U-Nets ensemble aggregation.

PURPOSE: This work presents our contribution to one of the data challenges organized by the French Radiology Society during the Journées Francophones de Radiologie. This challenge consisted in segmenting the kidney cortex from coronal computed tomography (CT) images, cropped around the cortex. MATERIALS AND METHODS: We chose to train an ensemble of fully-convolutional networks and to aggregate their prediction at test time to perform the segmentation. An image database was made available in 3 batches. A first training batch of 250 images with segmentation masks was provided by the challenge organizers one month before the conference. An additional training batch of 247 pairs was shared when the conference began. Participants were ranked using a Dice score. RESULTS: The segmentation results of our algorithm match the renal cortex with a good precision. Our strategy yielded a Dice score of 0.867, ranking us first in the data challenge. CONCLUSION: The proposed solution provides robust and accurate automatic segmentations of the renal cortex in CT images although the precision of the provided reference segmentations seemed to set a low upper bound on the numerical performance. However, this process should be applied in 3D to quantify the renal cortex volume, which would require a marked labelling effort to train the networks.

Automatic knee meniscus tear detection and orientation classification with Mask-RCNN.

PURPOSE: This work presents our contribution to a data challenge organized by the French Radiology Society during the Journées Francophones de Radiologie in October 2018. This challenge consisted in classifying MR images of the knee with respect to the presence of tears in the knee menisci, on meniscal tear location, and meniscal tear orientation. MATERIALS AND METHODS: We trained a mask region-based convolutional neural network (R-CNN) to explicitly localize normal and torn menisci, made it more robust with ensemble aggregation, and cascaded it into a shallow ConvNet to classify the orientation of the tear. RESULTS: Our approach predicted accurately tears in the database provided for the challenge. This strategy yielded a weighted AUC score of 0.906 for all three tasks, ranking first in this challenge. CONCLUSION: The extension of the database or the use of 3D data could contribute to further improve the performances especially for non-typical cases of extensively damaged menisci or multiple tears.

Evaluation of cortical segmentation pipelines on clinical neonatal MRI data.

Magnetic Resonance Imaging (MRI) can provide 3D morphological information on brain structures. Such information is particularly relevant for carrying out morphometric brain analysis, especially in the newborn and in the case of prematurity. However, 3D neonatal MRI acquired in clinical environments are low-resolution, anisotropic images, making segmentation a challenging task. In this context, preprocessing techniques aim to increase the image resolution. Interpolation techniques were classically used; super-resolution (SR) techniques have recently appeared as an emerging alternative. In this paper, we evaluate the performance of different SR methods against the classical interpolation in the application of neonatal cortex segmentation. Additionally, we assess the robustness of different segmentation methods for each estimation of high resolution MRI input. Results are evaluated both qualitatively and quantitatively with neonatal clinical MRI.

Nonequilibrium Mass Transport in the 1D Fermi-Hubbard Model.

We experimentally and numerically investigate the sudden expansion of fermions in a homogeneous one-dimensional optical lattice. For initial states with an appreciable amount of doublons, we observe a dynamical phase separation between rapidly expanding singlons and slow doublons remaining in the trap center, realizing the key aspect of fermionic quantum distillation in the strongly interacting limit. For initial states without doublons, we find a reduced interaction dependence of the asymptotic expansion speed compared to bosons, which is explained by the interaction energy produced in the quench.

Localized Magnetic Moments with Tunable Spin Exchange in a Gas of Ultracold Fermions.

We report on the experimental realization of a state-dependent lattice for a two-orbital fermionic quantum gas with strong interorbital spin exchange. In our state-dependent lattice, the ground and metastable excited electronic states of ^{173}Yb take the roles of itinerant and localized magnetic moments, respectively. Repulsive on-site interactions in conjunction with the tunnel mobility lead to spin exchange between mobile and localized particles, modeling the coupling term in the well-known Kondo Hamiltonian. In addition, we find that this exchange process can be tuned resonantly by varying the on-site confinement. We attribute this to a resonant coupling to center-of-mass excited bound states of one interorbital scattering channel.

[Animal ethics in the 19th century and Swiss animal protection law]. / Tierethik im 19. Jahrhundert und schweizerisches Tierschutzrecht.

INTRODUCTION: The development of animal ethics and animal rights from the antiquity up to modern times is described. The relationship of humans to animals was primarily based on fear and animal cult, developed by the domestication to a partnership. The philosophers of the early modern age denied the animals the reason, what was disadvantageous to the position of the animals in the society and the behavior of humans to the animals. By the end of the 19th century the animal protection concept developed with numerous postulates for legal regulations. With the Swiss animal protection law, which came into force in 1981, most of the postulates could be realised. It is shown, how animal protection has developed since that time.

Spin Pumping and Measurement of Spin Currents in Optical Superlattices.

We report on the experimental implementation of a spin pump with ultracold bosonic atoms in an optical superlattice. In the limit of isolated double wells, it represents a 1D dynamical version of the quantum spin Hall effect. Starting from an antiferromagnetically ordered spin chain, we periodically vary the underlying spin-dependent Hamiltonian and observe a spin current without charge transport. We demonstrate a novel detection method to measure spin currents in optical lattices via superexchange oscillations emerging after a projection onto static double wells. Furthermore, we directly verify spin transport through in situ measurements of the spins' center-of-mass displacement.

Optimal control of complex atomic quantum systems.

Quantum technologies will ultimately require manipulating many-body quantum systems with high precision. Cold atom experiments represent a stepping stone in that direction: a high degree of control has been achieved on systems of increasing complexity. However, this control is still sub-optimal. In many scenarios, achieving a fast transformation is crucial to fight against decoherence and imperfection effects. Optimal control theory is believed to be the ideal candidate to bridge the gap between early stage proof-of-principle demonstrations and experimental protocols suitable for practical applications. Indeed, it can engineer protocols at the quantum speed limit - the fastest achievable timescale of the transformation. Here, we demonstrate such potential by computing theoretically and verifying experimentally the optimal transformations in two very different interacting systems: the coherent manipulation of motional states of an atomic Bose-Einstein condensate and the crossing of a quantum phase transition in small systems of cold atoms in optical lattices. We also show that such processes are robust with respect to perturbations, including temperature and atom number fluctuations.

INDIVIDUALISED CALCULATION OF TISSUE IMPARTED ENERGY IN BREAST TOMOSYNTHESIS.

The imparted energy to the glandular tissue in the breast (glandular imparted energy, GIE) is proposed for an improved assessment of the individual radiation-induced risk resulting from X-ray breast imaging. GIE is computed from an estimation of the quantity and localisation of glandular tissue in the breast. After a digital breast tomosynthesis (DBT) acquisition, the volumetric glandular content (volumetric breast density, VBD) is computed from the central X-ray projection. The glandular tissue distribution is determined by labelling the DBT voxels to ensure the conservation of the VBD. Finally, the GIE is calculated by Monte Carlo computation on the resulting tissue-labelled DBT volume. For verification, the method was applied to 10 breast-shaped digital phantoms made of different glandular spheres in an adipose background, and to a digital anthropomorphic phantom. Results were compared to direct GIE computations on the phantoms considered as 'ground-truth'. The major limitations in accuracy are those of DBT, in particular the limited z-resolution. However, for most phantoms, the results can be considered as acceptable.

Infants and young children modeling method for numerical dosimetry studies: application to plane wave exposure.

Numerical dosimetry studies require the development of accurate numerical 3D models of the human body. This paper proposes a novel method for building 3D heterogeneous young children models combining results obtained from a semi-automatic multi-organ segmentation algorithm and an anatomy deformation method. The data consist of 3D magnetic resonance images, which are first segmented to obtain a set of initial tissues. A deformation procedure guided by the segmentation results is then developed in order to obtain five young children models ranging from the age of 5 to 37 months. By constraining the deformation of an older child model toward a younger one using segmentation results, we assure the anatomical realism of the models. Using the proposed framework, five models, containing thirteen tissues, are built. Three of these models are used in a prospective dosimetry study to analyze young child exposure to radiofrequency electromagnetic fields. The results lean to show the existence of a relationship between age and whole body exposure. The results also highlight the necessity to specifically study and develop measurements of child tissues dielectric properties.

Neonatal brain MRI: how reliable is the radiologist's eye?

INTRODUCTION: White matter (WM) analysis in neonatal brain magnetic resonance imaging (MRI) is challenging, as demonstrated by the issue of diffuse excessive high signal intensity (DEHSI). We evaluated the reliability of the radiologist's eye in this context. METHODS: Three experienced observers graded the WM signal intensity on axial T2-weighted 1.5T images from 60 different premature newborns on 2 occasions 4 weeks apart with a semi-quantitative classification under identical viewing conditions. RESULTS: The intra- and inter-observer correlation coefficients were fair to moderate (Fleiss' kappa between 0.21 and 0.60). CONCLUSION: This is a serious limitation of which we need to be aware, as it can lead to contradictory conclusions in the challenging context of term-equivalent age brain MRI in premature infants. These results highlight the need for a semiautomatic tool to help in objectively analyzing MRI signal intensity in the neonatal brain.

Dynamical Quasicondensation of Hard-Core Bosons at Finite Momenta.

Long-range order in quantum many-body systems is usually associated with equilibrium situations. Here, we experimentally investigate the quasicondensation of strongly interacting bosons at finite momenta in a far-from-equilibrium case. We prepare an inhomogeneous initial state consisting of one-dimensional Mott insulators in the center of otherwise empty one-dimensional chains in an optical lattice with a lattice constant d. After suddenly quenching the trapping potential to zero, we observe the onset of coherence in spontaneously forming quasicondensates in the lattice. Remarkably, the emerging phase order differs from the ground-state order and is characterized by peaks at finite momenta ±(π/2)(ℏ/d) in the momentum distribution function.