A Riemann-Hilbert approach to rotating attractors

We construct rotating extremal black hole and attractor solutions in gravity theories by solving a Riemann-Hilbert problem associated with the Breitenlohner-Maison linear system. By employing a vectorial Riemann-Hilbert factorization method we explicitly factorize the corresponding monodromy matrices, which have second order poles in the spectral parameter. In the underrotating case we identify elements of the Geroch group which implement Harrison-type transformations which map the attractor geometries to interpolating rotating black hole solutions. The factorization method we use yields an explicit solution to the linear system, from which we do not only obtain the spacetime solution, but also an explicit expression for the master potential encoding the potentials of the infinitely many conserved currents which make this sector of gravity integrable

Leprosy and Kaposi Sarcoma Presenting as an Immune Reconstitution Inflammatory Syndrome in a Patient with AIDS

The simultaneous presence of infectious organisms within cutaneous lesions of Kaposi sarcoma in persons with AIDS has been demonstrated. We describe a patient with concurrent leprosy and Kaposi sarcoma presenting as an immune reconstitution inflammatory syndrome in the setting of AIDS

Fully automated grey and white matter segmentation of the cervical cord in vivo

We propose and validate a new fully automated spinal cord (SC) segmentation technique that incorporates two different multi-atlas segmentation propagation and fusion techniques: Optimized PatchMatch Label fusion (OPAL) and Similarity and Truth Estimation for Propagated Segmentations (STEPS). We collaboratively join the advantages of each method to obtain the most accurate SC segmentation. The new method reaches the inter-rater variability, providing automatic segmentations equivalents to inter-rater segmentations in terms of DSC 0.97 for whole cord for any subject

Atrophy computation in the spinal cord using the Boundary Shift Integral

In this work, we introduce a new pipeline based on the latest iteration of the BSI for computing atrophy in the SC and compare its results with the most popular atrophy measurements for this region, mean CSA. We demonstrated for the first time the use of BSI in the SC, as a sensitive, quantitative and objective measure of longitudinal tissue volume change. The BSI pipeline presented in this work is repeatable, reproducible and standardises a pipeline for computing SC atrophy

Fully automated grey and white matter spinal cord segmentation

Axonal loss in the spinal cord is one of the main contributing factors to irreversible clinical disability in multiple sclerosis (MS). In vivo axonal loss can be assessed indirectly by estimating a reduction in the cervical cross-sectional area (CSA) of the spinal cord over time, which is indicative of spinal cord atrophy, and such a measure may be obtained by means of image segmentation using magnetic resonance imaging (MRI). In this work, we propose a new fully automated spinal cord segmentation technique that incorporates two different multi-atlas segmentation propagation and fusion techniques: The Optimized PatchMatch Label fusion (OPAL) algorithm for localising and approximately segmenting the spinal cord, and the Similarity and Truth Estimation for Propagated Segmentations (STEPS) algorithm for segmenting white and grey matter simultaneously. In a retrospective analysis of MRI data, the proposed method facilitated CSA measurements with accuracy equivalent to the inter-rater variability, with a Dice score (DSC) of 0.967 at C2/C3 level. The segmentation performance for grey matter at C2/C3 level was close to inter-rater variability, reaching an accuracy (DSC) of 0.826 for healthy subjects and 0.835 people with clinically isolated syndrome MS