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Optimisation of radiological protection for operators working with fluoroscopically guided procedures has to be performed during the procedure, under varying and difficult conditions. The aim of the present study was to evaluate the impact of a system for real-time visualisation of radiation dose rate on optimisation of occupational radiological protection in fluoroscopically guided procedures. In
A search is conducted for a beyond-the-Standard-Model boson using events where a Higgs boson with mass 125 GeV decays to four leptons (ℓ = e or μ). This decay is presumed to occur via an intermediate state which contains one or two on-shell, promptly decaying bosons: H → ZX/XX → 4ℓ, where X is a new vector boson Zd or pseudoscalar a with mass between 1 and 60 GeV. The search uses pp collision data
We prospectively evaluated a combination of fungal biomarkers in adult haematology patients with focus on their clinical utility at different time points during the course of infection. In total, 135 patients were monitored once to twice weekly for serum (1-3)-ß-d-glucan (BG), galactomannan (GM), bis-methyl-gliotoxin and urinary d-arabinitol/l-arabinitol ratio. In all, 13 cases with proven or prob
Changes to the smallest structures of the distal lung are often the first sign of severe respiratory disease, but to date methods to detect and quantify these changes are limited. Chronic obstructive pulmonary disease (COPD) is currently estimated to be the third most common cause of death worldwide, but is to a large extent under-diagnosed, especially at early stages. This thesis explores a new m
Social interaction sensing and indoor positioning using are widely researched. However, many use cases only need to determine proximity, and not the exact location. In this paper, we describe two methods to determine which meeting each user is participating in using proximity data collected from a challenging real-world office.We show that the RSSI threshold approach to detecting proximity is not
A numerical formulation is provided for secondary ice production during fragmentation of freezing raindrops or drizzle. This is obtained by pooling laboratory observations from published studies and considering the physics of collisions. There are two modes of the scheme: fragmentation during spherical drop freezing (mode 1) and during collisions of supercooled raindrops with more massive ice (mod
Despite of having no explicit shape model, multi-atlas approaches to image segmentation have proved to be a top-performer for several diverse datasets and imaging modalities. In this paper, we show how one can directly incorporate shape regularization into the multi-atlas framework. Unlike traditional multi-atlas methods, our proposed approach does not rely on label fusion on the voxel level. Inst
Exoplanet interior modelling usually makes the assumption that the elemental abundances of a planet are identical to those of its host star. Host stellar abundances are good proxies of planetary abundances, but only for refractory elements. This is particularly true for terrestrial planets, as evidenced by the relative differences in bulk chemical composition between the Sun and the Earth and othe
Background and purpose — The nonagenarian (those aged 90 years and older) population is expected to double in the next 20 years. This demographic age quake may have a significant impact on the incidence of total knee arthroplasty (TKA), although current literature provides limited data. We examined death and revision rates, patient-reported outcomes (PROs) and bias on patient selection of nonagena
Background: A crucial step in image fusion for intraoperative guidance during endovascular procedures is the registration of preoperative computed tomography angiography (CTA) with intraoperative Cone Beam CT (CBCT). Automatic tools for image registration facilitate the 3D image guidance workflow. However their performance is not always satisfactory. The aim of this study is to assess the accuracy
Localization microscopy methods like Stochastic Optical Reconstruction Microscopy (STORM) are very well suited for exploring clustering of proteins, as the data inherently provide a list of molecular coordinates. Here we use state-of-art cluster analysis algorithms (DBSCAN) to explore the clustering behaviour of different affinity forms of the integrin LFA-1. It has been suggested that LFA-1 may f
Human body pose and shape estimation is an important and challenging task in computer vision. This paper presents a novel method for estimating 3D human body pose and shape from several RGB images, using detected joint positions in the images and based on a parametric human body model. Firstly, the 2D joint points of the RGB images are estimated using a deep neural network, which provides a strong
With the advent of cheap sensors and computing capabilities as well as better algorithms it is now possible to do structure from motion using crowd sourced data. Individual estimates of a map can be obtained using structure from motion (SfM) or simultaneous localization and mapping (SLAM) using e.g. images, sound or radio. However the problem of map merging as used for collaborative SLAM needs fur
In this paper we introduce a fast and robust structure-less alternative to full bundle adjustment. The method is based on optimizing algebraic errors for trilinear constraints from triplets of views. It is shown that the error generated by a triplet of views can be described by a fixed triangular matrix regardless of the number of feature correspondences between the views. The method has been eval
Objective. To investigate baseline levels of 12 serum biomarkers that constitute a multibiomarker disease activity test, as predictors of response to methotrexate (MTX) in patients with early rheumatoid arthritis (eRA). Methods. In 298 patients from the Swedish Pharmacotherapy (SWEFOT) clinical trial, baseline serum levels of 12 proteins were analyzed for association with disease activity based on
Learning a computationally efficient kernel from data is an important machine learning problem. The majority of kernels in the literature do not leverage the geometry of the data, and those that do are computationally infeasible for contemporary datasets. Recent advances in approximation techniques have expanded the applicability of the kernel methodology to scale linearly with the data size. Data
The recently introduced method of `signal apparition' offers a fundamentally different approach to separation of multiple interfering sources, by using a periodic sequence of source signatures along one source line. This leads to exact separation of signals in diamond-shaped regions of the frequency-wavenumber domain which are twice as large compared to those recovered by other methods. In this pa
In this paper we study the problem of estimating receiver and sender positions from time-difference-of-arrival measurements, assuming an unknown constant time-difference-of-arrival offset. This problem is relevant for example for repetitive sound events. In this paper it is shown that there are three minimal cases to the problem. One of these (the five receiver, five sender problem) is of particul
