Linköping University

About: Linköping University is a education organization based out in Linköping, Sweden. It is known for research contribution in the topics: Population & Thin film. The organization has 15671 authors who have published 50013 publications receiving 1542189 citations.

Rapid magnetic resonance quantification on the brain: Optimization for clinical usage.

Abstract: A method is presented for rapid simultaneous quantification of the longitudinal T1 relaxation, the transverse T2 relaxation, the proton density (PD), and the amplitude of the local radio frequency ...

Space, time and visual analytics

Abstract: Visual analytics aims to combine the strengths of human and electronic data processing. Visualisation, whereby humans and computers cooperate through graphics, is the means through which this is achieved. Seamless and sophisticated synergies are required for analysing spatio-temporal data and solving spatio-temporal problems. In modern society, spatio-temporal analysis is not solely the business of professional analysts. Many citizens need or would be interested in undertaking analysis of information in time and space. Researchers should find approaches to deal with the complexities of the current data and problems and find ways to make analytical tools accessible and usable for the broad community of potential users to support spatio-temporal thinking and contribute to solving a large range of problems.

Adaptive Decontamination of the Training Set: A Unified Formulation for Discriminative Visual Tracking

Abstract: Tracking-by-detection methods have demonstrated competitive performance in recent years. In these approaches, the tracking model heavily relies on the quality of the training set. Due to the limited amount of labeled training data, additional samples need to be extracted and labeled by the tracker itself. This often leads to the inclusion of corrupted training samples, due to occlusions, misalignments and other perturbations. Existing tracking-by-detection methods either ignore this problem, or employ a separate component for managing the training set. We propose a novel generic approach for alleviating the problem of corrupted training samples in tracking-bydetection frameworks. Our approach dynamically manages the training set by estimating the quality of the samples. Contrary to existing approaches, we propose a unified formulation by minimizing a single loss over both the target appearance model and the sample quality weights. The joint formulation enables corrupted samples to be downweighted while increasing the impact of correct ones. Experiments are performed on three benchmarks: OTB-2015 with 100 videos, VOT-2015 with 60 videos, and Temple-Color with 128 videos. On the OTB-2015, our unified formulation significantly improves the baseline, with a gain of 3:8% in mean overlap precision. Finally, our method achieves state-of-the-art results on all three datasets.

Risk and case characteristics of tuberculosis in rheumatoid arthritis associated with tumor necrosis factor antagonists in Sweden.

Abstract: Objective. Because treatment with tumor necrosis factor (TNF) antagonists may increase the risk of tuberculosis (TB), and because knowledge of the risk of TB in rheumatoid arthritis (RA) not treated with biologics is scarce and of uncertain generalizability to low-risk populations, this study sought to determine the risk of TB among Swedish patients with RA. Methods. Using data from Swedish nationwide and population-based registers and data from an ongoing monitoring program of TNF antagonists, the relative risks of TB in patients with RA (versus the general population) and of TB associated with TNF antagonists (versus RA patients not treated with biologics) were determined by comparing the incidence of hospitalization for TB in 3 RA cohorts and 2 general population cohorts from 1999 to 2001. We also reviewed the characteristics of all reported cases of TB in RA patients treated with TNF antagonists in Sweden and calculated the incidence of TB per type of TNF antagonist between 1999 and 2004. Results. During 1999-2001, RA patients who were not treated with TNF antagonists were at increased risk of TB versus the general population (relative risk 2.0, 95% confidence interval [95% CI] 1.2-3.4). RA patients treated with TNF antagonists had a 4-fold increased risk of TB (relative risk 4.0, 95% CI 1.3-12) versus RA patients not treated with TNF antagonists. The reported TB cases during 1999-2004 in RA patients exposed to TNF antagonists (9 infliximab, 4 etanercept, 2 both) were predominantly pulmonary. TB occurred up to 3 years following the start of treatment. Conclusion. Irrespective of whether TNF antagonists are administered, Swedish patients with RA are at increased risk of TB. During 1999-2001, TNF antagonists were associated with an increased risk of TB, up to 4-fold in magnitude. This increased risk may persist over time during treatment and is related to both infliximab and etanercept.

Laser speckle contrast imaging: theoretical and practical limitations

Abstract: When laser light illuminates a diffuse object, it produces a random interference effect known as a speckle pattern. If there is movement in the object, the speckles fluctuate in intensity. These fluctuations can provide infor- mation about the movement. A simple way of accessing this information is to image the speckle pattern with an exposure time longer than the shortest speckle fluctuation time scale—the fluctuations cause a blurring of the speckle, leading to a reduction in the local speckle contrast. Thus, velocity distributions are coded as speckle con- trast variations. The same information can be obtained by using the Doppler effect, but producing a two-dimen- sional Doppler map requires either scanning of the laser beam or imaging with a high-speed camera: laser speckle contrast imaging (LSCI) avoids the need to scan and can be performed with a normal CCD- or CMOS-camera. LSCI is used primarily to map flow systems, especially blood flow. The development of LSCI is reviewed and its lim- itations and problems are investigated. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.